text:
|Publication number
|Publication type
|Application number
|Publication date
|Apr 21, 1998
|Filing date
|Apr 18, 1995
|Priority date
|Apr 18, 1995
|Fee status
|Also published as
|Publication number
|Navin Chaddha
|Original Assignee
|Sun Microsystems, Inc.
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (8), Referenced by (136), Classifications (30), Legal Events (4)
|External Links: USPTO, USPTO Assignment, Espacenet
The present invention relates generally to client decoders for use with video delivery systems, and more specifically to client decoders for use in video delivery systems in which video may be delivered scalably, so as to maximize use of network resources and to minimize user-contention conflicts.
It is known in the art to use server-client networks to provide video to end users, wherein the server issues a separate video stream for each individual client.
A library of video sources is maintained at the server end. Chosen video selections are signal processed by a server encoder stored on digital media, and are then transmitted over a variety of networks, perhaps on an basis that allows a remote viewer to interact with the video. The video may be stored on media that includes magnetic disk, CD-ROM, and the stored information can include video, speech, and images. As such, the source video information may have been stored in one of several spatial resolutions (e.g., 160×120, 320×240, 640×480 pixels), and temporal resolutions (e.g., 1 to 30 frames per second). The source video may present bandwidths whose dynamic range can vary from 10 Kbps to 10 Mbps.
The signal processed video is transmitted to the clients (or decoders) over one or more delivery networks that may be heterogeneous, e.g., have widely differing bandwidths. For example, telephone delivery lines can transmit at only a few tens of Kbps, an ISDN network can handle 128 Kbps, ethernet at 10 Mbps, whereas ATM networks handle even higher transmission rates.
Although the source video has varying characteristics, prior art video delivery systems operate with a system bandwidth that is static or fixed. Although such system bandwidths are fixed, in practice, the general purpose computing environment associated with the systems are dynamic, and variations in the networks can also exist. These variations can arise from the outright lack of resources (e.g., limited network bandwidth and processor cycles), contention for available resources due to congestion, or a user's unwillingness to allocate needed resources to the task.
Prior art systems tend to be very computationally intensive, especially with respect to decoding images of differing resolutions. An encoder may transmit a bit stream of, say, 320×240 pixel resolution, whereas the decoder requires 160×120 pixel resolution. Decoding, in the prior art, requires that several processes be invoked, including decompression, entropy coding, quantization, discrete cosine transformation and down-sampling. Collectively, these process steps take too long to be accomplished in real-time.
Color conversions, e.g., YUV-to-RGB are especially computationally intensive, in the prior art. In another situation, an encoder may transmit 24 bits, representing 16 million colors, but a recipient decoder may be coupled to a PC having an 8 bit display, capable of only 256 colors. The decoder must then dither the incoming data, which is a computationally intensive task. Prior art decoders also take too long to complete operations such as color palletization to operate in real-time.
Unfortunately, fixed bandwidth prior art systems cannot make full use of such dynamic environments and system variations. The result is slower throughput and more severe contention for a given level of expenditure for system hardware and software. When congestion (e.g., a region of constrained bandwidth) is present on the network, packets of transmitted information will be randomly dropped, with the result that no useful information may be received by the client.
Video information is extremely storage intensive, and compression is necessary during storage and transmission. Although scalable compression would be beneficial, especially for browsing in multimedia video sources, existing compression systems do not provide desired properties for scalable compression. By scalable compression it is meant that a full dynamic range of spatial and temporal resolutions should be provided on a single embedded video stream that is output by the server over the network(s). Acceptable software-based scalable techniques are not found in the prior art. For example, the MPEG-2 compression standard offers limited extent scalability, but lacks sufficient dynamic range of bandwidth, is costly to implement in software, and uses variable length codes that require additional error correction support.
Further, prior art compression standards typically require dedicated hardware at the encoding end, e.g., an MPEG board for the MPEG compression standard. While some prior art encoding techniques are software-based and operate without dedicated hardware (other than a fast central processing unit), known software-based approaches are too computational intensive to operate in real-time. For example, JPEG software running on a SparcStation 10 workstation can handle only 2-3 frames/second, e.g., about 1% of the frame/second capability of the present invention.
Considerable video server research in the prior art has focussed on scheduling policies for on-demand situations, admission control, and RAID issues. Prior art encoder operation typically is dependent upon the characteristics of the client decoders. Simply stated, relatively little work has been directed to video server systems operable over heterogeneous networks having differing bandwidth capabilities, where host decoders have various spatial and temporal resolutions.
In summary, there is a need for a video delivery system that provides end-to-end video encoding such that the server outputs a single embedded data stream from which decoders may extract video having different spatial resolutions, temporal resolutions and data rates. The resultant video compression would be bandwidth scalable and thus deliverable over heterogeneous networks whose transmission rates vary from perhaps 10 Kbps to 10 Mbps. Such a system should accommodate lower bandwidth links or congestion, and should permit the encoder to operate independently of decoder capability or requirements.
Preferably the decoder should be software-based (e.g., not require specialized dedicated hardware beyond a computing system) and should permit real-time decompression. Alternatively, the decoder should be implementable in hardware, using relatively inexpensive components. The system should permit user selection of a delivery bandwidth to choose the most appropriate point in spatial resolution, temporal resolution, data-rate and in quality space. The system should also provide subjective video quality enhancement, and should include error resilience to allow for communication errors.
The present invention provides such a decoder an end-to-end scalable video delivery system.
In a first embodiment, the present invention provides a software-based, rapidly operating decoder of low computational complexity for use with an end-to-end scalable video delivery system whose software-based server-encoder operates independently of the capabilities and requirements of the software-based decoder(s). The decoder operates in conjunction with a central processor unit ("CPU") and relies upon stored look-up tables containing preprocessed operations including color conversion, dithering, color palletization, interpolation, decimation, edge enhancement, and the like. In a second embodiment, the decoder functions are permanently stored in a read-only memory ("ROM") that operates in conjunction with a relatively simple central processor unit.
The encoder uses a scalable compression algorithm based upon Laplacian pyramid decomposition. An original 640×480 pixel image is decimated to produce a 320×240 pixel image that is itself decimated to yield a 160×120 pixel base image that is encoder-transmitted. This base image is then compressed to form a 160×120 pixel base layer that is decompressed and up-sampled to produce an up-sampled 320×240 pixel image. The up-sampled 320×240 pixel image is then subtracted from the 320×240 pixel image to provide an error image that is compressed as transmitted as a first enhancement layer. The 160×120 pixel decompressed image is also up-sampled to produce an up-sampled 640×480 pixel image that is subtracted from the original 640×480 pixel image to yield an error image that is compressed and transmitted as a second enhancement layer.
Collectively the base layer, and first and second enhancement layers comprise the single embedded bitstream that may be multicast over heterogeneous networks that can range from telephone lines to wireless transmission. Packets within the embedded bit-stream preferably are prioritized with bits arranged in order of visual importance. The resultant bit stream is easily rescaled by dropping less important bits, thus providing bandwidth scalability dynamic range from a few Kbps to many Mbps. Further, such embedded bit stream permits the server system to accommodate a plurality of users whose decoder systems have differing characteristics. The transmitting end also includes a market-based mechanism for resolving conflicts in providing an end-to-end scalable video delivery service to the user.
At the receiving end, the present invention comprises decoders, software-based or contained in ROM, of varying characteristics that extract different streams at different spatial and temporal resolutions from the single embedded bit stream. Decoding a 160×120 pixel image involves only decompressing the base layer 160×120 pixel image. Decoding a 320×240 pixel image involves decompressing and up-sampling (e.g., interpolating) the base layer to yield a 320×240 pixel image to which is added error data in the first enhancement layer following its decompression. To obtain a 640×480 pixel image, the decoder up-samples the up-sampled 320×240 pixel image, to which is added error data in the second enhancement layer, following its decompression.
Because decoding requires only additions and look-ups from a table stored in a small (12 Kb) memory, decoding occurs in real-time. Further, the decoder functions may be stored in a 12 Kb ROM that operates under control of a simple CPU. Subjective quality of the compressed images preferably is enhanced using perceptual distortion measures. The system also provides joint-source channel coding capability on heterogenous networks. The look-up table or codebook includes the inverse perceptual weighting (preprocessed) and the inverse transform (preprocessed). This permits decoding to involve merely a look-up operation and addition. Decoding according to the present invention permits the codewords within the look-up table or codebook to include preprocessed color conversion, dithering, color palletization, edge-enhancement, decimation, and interpolation.
Other features and advantages of the invention will appear from the following description in which the preferred embodiments have been set forth in detail, in conjunction with the accompanying drawings.
FIG. 1 is a block diagram of an end-to-end scalable video system, accord to the present invention;
FIG. 2 is a block/flow diagram depicting a software-based encoding technique for generating a scalable embedded video stream, according to the present invention;
FIG. 3 is a block/flow diagram depicting a decoding technique to recover scalable video from a single embedded video stream, according to the present invention.
FIG. 1 depicts an end-to-end scalable video delivery system including decoder(s) 40, 40' according to the present invention. Decoders 40, 40' may be software-based low computational complexity units, or may be implemented in hardware. A source of audio and video information 10 is coupled to a server or encoder 20. The encoder signal processes the information to produce a single embedded information stream that is transmitted via homogeneous networks 30, 30' to one or more target clients or software-based decoder systems 40, 40', which use minimal central processor unit resources. Network transmission may be through a so-called network cloud 50, from which the single embedded information stream is multicast to the decoders, or transmission to the decoders 40' may be point-to-point.
The networks are heterogeneous in that they have widely varying bandwidth characteristics, ranging from as low as perhaps 10 Kbps for telephones, to 100 Mbps or more for ATM networks. As will be described, the single embedded information stream is readily scaled, as needed, to accommodate a lower bandwidth network link or to adapt to network congestion.
Server 20 includes a central processor unit ("CPU") with associated memory, collectively 55, scalable video encoder 60, according to the present invention, a mechanism 70 for synchronizing audio, video and textual information, a mechanism 80 for arranging the information processed by the scalable video encoder onto video disks 90 (or other storage media). Storage 100 is also provided for signal processed audio information. Software comprising the scalable video encoder 60 preferably is digitally stored within server 20, for example, within the memory associated with CPU unit 55.
An admission control mechanism 110 is coupled to the processed video storage 90, as is a communication error recovery mechanism 120 for handling bit errors or packet cell loss. The decoder algorithm provides error resilience allowing for such communication errors. The server communicates with the heterogeneous network(s) through a network interface 130.
Scalable video encoder 60 preferably is implemented in software only (e.g., no dedicated hardware), and generates a single embedded information stream. Encoder 60 employs a new video coding algorithm based on a Laplacian pyramidal decomposition to generate the embedded information stream. (Laplacian pyramids are a form of compression known to those skilled in the art, and for that reason further details are not presented here.) The generated embedded stream allows server 20 to host decoders 40, 40' having various spatial and temporal resolutions, without the server having to know the characteristics of the recipient decoder(s).
Encoding is shown in FIG. 2. In overview, the base layer is coding by doing a discrete cosine transform ("DCT") followed by perceptual-weighting, followed by vector quantization. The base layer is coded and is interpolated to the next higher layer, where the error difference is taken with respect to the original image at that layer. The error is again coded using DCT followed by perceptual weighting, followed by vector quantization. The process is repeated for the next higher level image.
More specifically, as shown in FIG. 2, an original 640×480 pixel image 200 from source 10 is coupled to the scalable video encoder 60. At process step 210, this image is decimated (e.g., filtered and sub-sampled) to 320×240 pixels (image 220), step 210, and at process step 230 image 220 is decimated to produce a base layer 160×120 pixel image 240 for encoding by encoder 60.
For the 160×120 pixel base layer, encoding preferably is done on a 2×2 blocks (e.g., two adjacent pixels on one line, and two adjacent pixels on a next line defining the block) with DCT followed by tree-structured vector quantization ("TSVQ") of the results of that transform. For the 320×240 first enhancement layer, encoding is done on 4×4 blocks, with DCT followed by TSVQ, and for the 640×480 pixel enhancement layer, encoding is done on 8×8 blocks, again with DCT followed by TSVQ.
At step 250, the 160×120 pixel base image 240 is compressed to form a 160×120 pixel base layer 260 and then at step 270 is decompressed. The resulting decompressed image 280 is up-sampled by interpolation step 290 to produce an up-sampled 320×240 pixel image 300.
At summation step 310, the up-sampled 320×240 pixel image 300 is subtracted from the 320×240 pixel image 220 to give an error image 320. At step 330 the error image 320 is compressed and then transmitted as a first enhancement 640×480 pixel layer 340.
The 160×120 pixel decompressed image 280 is also up-sampled at step 350 to produce an up-sampled 640×480 pixel image 360. At summation step 370, the up-sampled 640×480 pixel image 360 is subtracted from the original 640×480 pixel image 200 to yield an error image 380. At step 390, the error image 380 is compressed to yield a second enhancement 320×240 pixel layer 400 that is transmitted. Collectively, layers 260, 340 and 400 comprise the embedded bit-stream generated by the scalable video encoder 60.
Thus, it is appreciated from FIG. 2 that a scalable video encoder 60 according to the present invention encodes three image resolutions. The transmitted base layer 260 has compressed data for the compressed 160×120 pixel image 240. The first enhancement layer 340 has error data for the compressed 320×240 pixel image 220, and the second enhancement layer 400 has error data for the compressed 640×480 pixel image 200.
Thus, the present invention uses vector quantization across transform bands to embed coding to provide bandwidth scalability with an embedded bit stream. Vector quantization techniques are known in the art. See, for example, A. Gerso and R. M. Gray, "Vector Quantization and Signal Compression", Kluwer Academic Press, 1992.
Embedded coding and vector quantization may each be performed by tree-structured vector quantization methods e.g., by a successive approximation version of vector quantization ("VQ"). In ordinary VQ, the codewords lie in an unstructured codebook, and each input vector is mapped to the minimum distortion codeword. Thus, VQ induces a partition of a input space into Voronoi encoding regions.
By contrast, when using TSVQ, the codewords are arranged in a tree structure, and each input vector is successively mapped (from the root node) to the minimum distortion child node. As such, TSVQ induces a hierarchical partition, or refinement of the input space as three depth of the tree increases. Because of this successive refinement, an input vector mapping to a leaf node can be represented with high precision by the path map from the root to the leaf, or with lower precision by any prefix of the path.
TSVQ produces an embedded encoding of the data wherein if the depth of the tree is R and the vector dimension is k, bit rates O/k, . . . , R/k can all be achieved. To achieve further compression, the index-planes can be run-length coded followed by entropy coding. Algorithms for designing TSVQs and its variants have been studied extensively. The Gerso and Grey treatise cited above provides a background survey of such algorithms.
In the prior art, mean squared error typically is used as distortion measure, with discrete cosine transforms ("DCT") being followed by scalar quantization. By contrast, the present invention performs DCT after which whole blocks of data are subjected to vector quantization, preferably with a perception model. Subjectively meaningful distortion measures are used in the design and operation of the TSVQ. For this purpose, vector transformation is made using the DCT. Next, the following input-weighted squared error is applied to the transform coefficients: ##EQU1##
In the above equation, yj and yj are the components of the transformed vector y and of the corresponding reproduction vector y, whereas wj is a component of the weight vector depending in general on y. Stated differently, distortion is the weighted sum of squared differences between the coefficients of the original transformed vector and the corresponding reproduced vector.
According to the present invention, the weights reflect human visual sensitivity to quantization errors in different transform coefficients, or bands. The weights are input-dependent to model masking effects. When used in the perceptual distortion measure for vector quantization, the weights control an effective stepsize, or bit allocation, for each band. When the transform coefficients are vector quantized with respect to a weighted squared error distortion measure, the role played by weights w1, . . . , wk corresponds to stepsizes in the scalar quantization case. Thus, the perceptual model is incorporated into the VQ distortion measure, rather than into a stepsize or bit allocation algorithm. This permits the weights to vary with the input vector, while permitting the decoder to operate without requiring the encoder to transmit any side information about the weights.
In the first stage of the compression encoder shown in FIG. 2, an image is transformed using DCT. The second stage of the encoder forms a vector of the transformed block. Next, the DCT coefficients are vector quantized using a TSVQ designed with a perceptually meaningful distortion measure. The encoder sends the indices as an embedded stream with different index planes. The first index plane contains the index for the rate 1/k TSVQ codebook. The second index plane contains the additional index which along with the first index plane gives the index for the rate 2/k TSVQ codebook. The remaining index planes similarly have part of the indices for 3/k, 4/k, . . . , R/k TSVQ codebooks, respectively.
Such encoding of the indices advantageously produces an embedded prioritized bitstream. Thus, rate or bandwidth scalability is easily achieved by dropping index planes from the embedded bit-stream. At the receiving end, the decoder can use the remaining embedded stream to index a TSVQ codebook of the corresponding rate.
Frame-rate scalability can be easily achieved by dropping frames, as at present no interframe compression is implemented in the preferred embodiment of the encoder algorithm. The algorithm further provides a perceptually prioritized bit-stream because of the embedding property of TSVQ. If desired, motion estimation and/or conditional replenishment may also be incorporated into the system.
Scalable compression according to the present invention is also important for image browsing, multimedia applications, transcoding to different formats, and embedded television standards. By prioritizing packets comprising the embedded stream, congestion due to contention for network bandwidth, central processor unit ("CPU") cycles, etc., in the dynamic environment of general purpose computing systems can be overcome by intelligently dropping less important packets from the transmitted embedded stream.
Information layout on the video disk storage system 90 (see FIG. 1) preferably involves laying the video as two streams, e.g., the base layer and the first and second enhancement layer streams. In practice, it is not necessary to store the error signal for the 640×480 resolution, since fairly good quality video can be provided by bilinear interpolation of the 320×240 resolution images.
The base layer data is stored as a separate stream from the enhancement layer data on disk subsystem 90. This allows the system to admit more users when fewer users choose to receive the enhancement layer data. As will now be described, the base layer data is stored hierarchically, data for each frame being stored together. Each frame has a set of index planes corresponding to different number of bits used for the lookup.
The compressed stream comprises look-up indices with different number of bits depending on the bandwidth and quality requirement. The look-up indices for each frame are stored as groups of index planes pre-formatted with application level headers for network transmission. Preferably the four most significant bits of the lookup indices are stored together as the first section of the frame block. Then four additional 1-bit planes of look-up are stored in sequence, as separate sections of the frame block to provide lookup indices with 4, 5, 6, 7, 8 bits, respectively. The different look-up indices provide data streams with different bandwidth requirements.
With reference to FIG. 1, server 20 fetches the base signal frame block from the disk 90, transmits the selected sections on the network 30, 30'. The re-packing of the bit planes into look-up indices is left to the receiving application at the client-end of the system.
The error data is placed similarly as another data stream. The look-up indices preferably are stored as the most significant two bits of the look-up indices in the first section for each frame block in the bit stream. Then follow the second two bits of the look-up indices as the second section, followed in turn by four additional 1-bit sections of lookup indices that are stored to provide look-up indices with 2, 4, 5, 6, 7, 8 bits, respectively. Other encoding bit patterns might instead be used, however.
Preferably the video server uses RAID-like techniques to stripe each (data stream) across several drives. RAID design techniques are known in the art; e.g., see F. Tobagi, et al., "Streaming RAID--A disk array management system for video files," Proc. ACM Multimedia 1993. A RAID design allows for recovery from failure of any single disk without diminishing the capacity of the server. A RAID design removes any restriction on the number of active users of a given video title, as long as the multiple users can be accommodated within the server total bandwidth. That is, the usage can range from all active users receiving the same title at different offsets to all receiving different streams.
The streams of base and enhancement layer data preferably are striped in fixed size units across the set of drives in the RAID group, with parity placed on an additional drive. The selection of the parity drive is fixed since data updates are quite rare compared to the number of times the streams are read. The preferred striping policy keeps all of the look-up indices for an individual frame together on one disk. This allows for ease of positioning when a user single steps or fast-forwards the user's display, although there is a penalty in some loss of storage capacity due to fragmentation. Use of parity on the stripe level allows for quick recovery after a drive failure at the cost of using substantially more buffer space to hold the full exclusive-OR recovery data set.
In the present invention, the video server utilizes the planar bit stream format directly as the basis for the packet stream in the network layer. The embedded stream bits plus the application packet header are read from disk 90 and are transmitted on the network in exactly the same format. For example, in the preferred embodiment the base video layer has the four most significant bits of the look-up indices stored together. Thus, those bits are transmitted as one 2440 byte packet, and each additional index bit plane of the less significant bits is transmitted as a separate 640 byte packet.
The header preferably contains a frame sequence number, nominal frame rate, size, a virtual time stamp, and a bit plane type specifier sufficient to make each packet an identifiable stand-alone unit. The server uses the self identifying header to extract each bit plane group packet from the striped frame data retrieved from the disk subsystem.
The server also uses the header sequence and rate information as a means to pace the network transmission and disk read requests. The server uses a feedback loop to measure the processing and delivery time costs of the disk reads and queueing the network packets for transmission. The server then uses these measures to schedule the next disk read and packet transmission activities to match the video stream frame rate (i.e., at X milliseconds in the future start transmitting the next frame of video). The server can moderate the transmission rate based on slow down/speed-up feedback from the decoder.
With further reference to FIG. 1, at the receiving end, decoder(s) 40 according to the present invention include a central processing unit ("CPU") 140 that includes a CPU per se and associated memory including cache memory. Decoder(s) 40 further includes a mechanism 145 for synchronizing audio and video information from the incoming embedded stream, as well as audio and video decoders 150, 160. The output from these decoders is coupled to sound generator, e.g., a speaker, and to video displays 180.
If the decoders are software-based, the decoding process steps preferably are stored in memory, for example memory 140, for execution by the associated CPU. Alternatively, in applications where full CPU operations are not required, for example simple display applications, decoders according to the present invention may be implemented in hardware, e.g., in a simply CPU' and read-only memory ("ROM") unit 155. Within unit 155 is a relatively simple central processor unit CPU' that, collectively with the associated ROM, represents a hardware unit that may be produced for a few dollars.
Target decoder system 40 should be able to define at least 160×120, 320×240, 640×480 pixel spatial resolutions, and at least 1 to 30 frames per second temporal resolution. Decoder system 40 must also accommodate bandwidth scalability with a dynamic range of video data from 10 kbps to 10 kbps to 10 Mbps. According to the present invention, video encoder 60 provides a single embedded stream from which different streams at different spatial and temporal resolutions and different data rates can be extracted by decoders 40, depending on decoder capabilities and requirements. However, as noted, encoder embedding is independent of the characteristics of the decoder(s) that will receive the single embedded information stream.
For example, decoder 40 can include search engines that permit a user to browse material for relevant segments, perhaps news, that the user may then select for full review. Within server 20, video storage 90 migrates the full resolution, full frame rate news stories based on their age and access history from disk to CD ROM to tape, leaving lower resolution versions behind to support the browsing operation. If a news segment becomes more popular or important, the higher resolution can then be retrieved and stored at a more accessible portion of the storage hierarchy 90.
The decoders merely use the indices from the embedded bit-stream to look-up from a codebook that is designed to make efficient use of the cache memory associated with the CPU unit 140. According to the present invention, video stream decoding is straightforward, and consists of loading the codebooks into the CPU cache memory, and performing look-ups from the stored codebook tables. In practice, the codebook may be stored in less than about 12 Kb of cache memory.
As noted, alternatively, unit 155 may include a small, e.g., about 12 Kb ROM, that under control of a simply processor unit CPU' inexpensively provides decoder operations in applications where the full function of a more complex processor (such as the CPU associated with unit 140) are not needed. It is understood from FIG. 1 that a hardware-based (e.g., ROM-based) decoder embodiment would include unit 155 but not unit 140.
Video decoder 160 uses a Laplacian pyramid decoding algorithm, and preferably can support up to three spatial resolutions, i.e., 160×120 pixels, 320×240 pixels, and 640×480 pixels. Further, decoder 160 can support any frame rate, as the frames are coded independently by encoder 60.
The decoding methodology is shown in FIG. 3. To decode a 160×120 pixel image, decoder 160 at method step 410 need only decompress the base layer 160×120 pixel image 260. The resultant image 430 is copied to video monitor (or other device) 180. APPENDIX 1, attached hereto, is a sample of decompression as used with the present invention.
To obtain a 320×240 pixel image, decoder 160 first decompresses (step 410) the base layer 260, and then at step 440 up-samples to yield an image 450 having the correct spatial resolution, e.g., 320×240 pixels. Next, at step 460, the error data in the first enhancement layer 340 is decompressed. The decompressed image 470 is then added at step 480 to up-sampled base image 450. The resultant 320×240 pixel image 490 is coupled by decoder 160 to a suitable display mechanism 180.
To obtain a 640×480 pixel image, the up-sampled 320×240 pixel image 450 is up-sampled at step 500 to yield an image 510 having the correct spatial resolution, e.g., 640×480 pixels. Next, at step 520, the error data in the second enhancement layer 400 is decompressed. The decompressed image 530 is added at step 540 to the up-sampled base image 510. The resultant 640×480 pixel image 550 is coupled by decoder 160 to a suitable display mechanism 180.
As seen from FIG. 3 and the above-description, it will be appreciated that obtaining the base layer from the embedded bit stream requires only look-ups, whereas obtaining the enhancement layers involves performing look-ups of the base and error images, followed by an addition process. The decoder is software-based and operates rapidly in that all decoder operations are actually performed beforehand, i.e., by preprocessing. The TSVQ decoder codebook contains the inverse DCT performed on the codewords of the encoder codebook.
Thus, at the decoder there is no need for performing inverse block transforms. Color conversion, i.e., YUV to RGB, is also performed as a pre-processing step by storing the corresponding color converted codebook. To display video on a limited color palette display, the resulting codewords of the decoder codebook are quantized using a color quantization algorithm. One such algorithm has been proposed by applicant Chaddha et al., "Fast Vector Quantization Algorithms for Color Palette Design Based on Human Vision Perception," accepted for publication IEEE Transactions on Image Processing.
According to the present invention, color conversion involves forming a RGB or YUV color vector from the codebook codewords, which are then color quantizing to the required alphabet size. Thus, the same embedded index stream can be used for displaying images on different alphabet decoders that have the appropriate codebooks with the correct alphabet size, e.g., 1-bit to 24-bit color.
On the receiving end, the video decoder 40, 40' is responsible for reassembly of the lookup indices from the packets received from the network. If one of the less significant index bit plane packets is somehow lost, the decoder uses the more significant bits to construct a shorter look-up table index. This yields a lower quality but still recognizable image.
The use of separately identified packets containing index bit planes makes it possible for networks to easily scale the video as a side effect of dropping less important packets. In networks providing QOS qualifiers such as ATM, multiple circuits can be used to indicate the order in which packets should be dropped (i.e., the least significant bit plane packets first). In an IP router environment, packet filters can be constructed to appropriately discard less important packets. For prioritized networks, the base layer will be sent on the high priority channel while the enhancement layer will be sent on the low priority channel. To provide error resiliency, using a fixed-rate coding scheme with some added redundancy allows robustness in the event of packet loss.
It will be appreciated that a server according to the present invention can support two usage scenarios: point-to-point demand (e.g., networks 30', decoders 40' in FIG. 1), or multicast (e.g., network cloud 50, networks 30, decoders 40 in FIG. 1).
In a point-to-point demand environment, each destination system decoder presents its specific requirements to the server. The server then sends the selected elements of the embedded stream across the network to the destination. A separate network stream per destination allows the user to have VCR style functionality such as play/stop/rewind fast forward/fast reverse. If congestion occurs on the network, the routers and switches can intelligently drop packets from the embedded stream to give a lesser number of lookup bits.
In a multicast environment, the server, which has no information about the destination decoders, outputs the entire embedded stream for the different resolutions and rates onto the network as a set of trees. In the preferred embodiment, there may be one to eleven trees, depending on the granularity of traffic control desired. The primary traffic management is performed during the construction of the unicast trees, by not adding branches of the trees carrying the less important bit streams to the lower bandwidth networks. The network in this case takes care of bandwidth mismatches by not forwarding packets to the networks which are not subscribed to a particular tree. Switches and routers can still react to temporary congestion by intelligently dropping packets from the embedded stream to deliver fewer bits of look-up.
The delivery system treats the audio track as a separate stream that is stored on disk 100 and transmitted across the network as a separate entity. The audio format supports multiple data formats from 8 KHz telephony quality (8 bit mu-law) to 48 KHz stereo quality audio (2 channel, 16 bit linear samples). In practice, many video clips may have 8 KHz telephone audio, to permit material distribution over medium-to-low bandwidth networks. The server can store separate high and low quality audio tracks, and transmit the audio track selected by the user. As the audio transits the network on a separate circuit, the audio can easily be given a higher QOS than the video streams. Rather than further load the networks with duplicate audio packets, as is known in the prior art, in the present invention the audio is ramped down to silence when packets are overly delayed or lost.
As the audio and video are delivered via independent mechanisms to the decoding system, the two streams must be synchronized by mechanism 145 for final presentation to the user. At the decoder, the receiving threads communicate through the use of a shared memory region, into which the sequence information of the current audio and video display units are written.
The human perceptual system is more sensitive to audio dropouts than to video drops, and audio is more difficult than video to temporarily reprocess. Thus, the decoder preferably uses the audio coder as the master clock for synchronization purposes. As the streams progress, the decoder threads post the current data items' sequence information onto a "blackboard" or scratchpad portion of memory associated with CPU unit 140. The slave threads (such as the video decoder) use the posted sequence information of the audio stream to determine when their data element should be displayed. The slave threads then delay until the appropriate time if the slave is early (e.g., more than 80 milliseconds ahead of the audio). If the slave data is too late (e.g., more than 20 milliseconds behind the audio), then it is discarded on the assumption that continuing to process late data will delay more timely data.
The video decoder can optionally measure the deviation from the desired data delay rate and send speed-up and slow-down indications back to the video server. This process synchronizes streams whose elements arrive in a timely fashion and does not allow a slow stream to impede the progress of the other streams.
In the event of scarcity of resources, some global prioritization of user requests must take place to guard against overload collapse. In a practical system, payment for services and resources may be used to define the overall value of each resource allocation decision. Given these values, a total ordering of the user requests can be made, e.g., by admission control 110, and the less important requests can be dropped. The user specifies what he or she is willing to pay for a given service. This proposed amount and the required associated resources (network and disk bandwidth) are submitted to an electronic market, e.g., admission control 110, which uses micro-economic models to decide what amount of bandwidth resource is available to the user. Such techniques are known in the art, e.g., M. Miller, "Extending markets inward," Bionomics Conference, San Francisco, Calif. (Oct. 1994).
For the particular bandwidth required, a table is indexed to find the best possible combination of spatial resolution, frame rate and data rate (number of bits of look-up to be used) to give the best quality of decompressed video. Preferably such table is built using a subjective distortion measure, such as described by N. Chaddha and T. H. Y. Meng, "Psycho-visual based distortion measures for image and video compression", Proc. of Asilomar Conference on Signals, Systems and Computers, Nov. 1993. Preferably, the user also has the option of specifying the spatial resolution, frame rate and bandwidth directly.
It will be appreciated that the described overall system combines a software-based encoder with an encoding compression algorithm, disk management, network transport, software-based decoder, and synchronization mechanism to provide an end-to-end scalable video delivery service. The service may be divided into three groups of components, comprising preprocessing, media server, and media player.
The processing components include audio capture, video capture, video compression, and a data stripping tool. The video is captured and digitized using single step VCR devices. Each frame is then compressed off-line (non-real time) using the encoding algorithm. At present, it takes about one second on a SparcStation 20 Workstation to compress a frame of video data, and single step VCR devices can step at a one frame per second rate permitting overlap of capture and compression.
The audio data preferably is captured as a single pass over the tape. The audio and video time stamps and sequence numbers are aligned by the data striping tool as the video is stored to facilitate later media synchronization. The audio and video data preferably are striped onto the disks with a user-selected stripe size. In a preferred embodiment, all of the video data on the server uses a 48 kilobyte stripe size, as 48 kilobytes per disk transfer provides good utilization at peak load with approximately 50% of the disk bandwidth delivering data to the media server components.
The media server components include a session control agent, the audio transmission agent, and the video transmission agent. The user connects to the session control agent on the server system and arranges to pay for the video service and network bandwidth. The user can specify the cost he/she is willing to pay and an appropriately scaled stream will be provided by the server. The session control agent (e.g., admission control mechanism 110) then sets up the network delivery connections and starts the video and audio transmission agents. The session control agent 110 is the single point of entry for control operations from the consumers remote control, the network management system, and the electronic market.
The audio and video transmission agents read the media data from the striped disks and pace the transmission of the data onto the network. The video transmission agent scales the embedded bit-stream in real-time by transmitting only the bit planes needed to reconstruct the selected resolution at the decoder. For example, a 320×240 stream with 8 bits of base, 4 bits of enhancement signal at 15 frames per second will transmit every other frame of video data with all 5 packets for each frame of the base and only two packets containing the four most significant bits of the enhancement layer resulting in 864 Kb of network utilization. The server sends the video and audio either for a point-to-point situation or a multicast situation.
The media player components are the software-based or ROM-based video decoder 40, 40', the audio receiver, and a user interface agent. The decoder receives the data from the network and decodes it using look-up tables and places the results onto the frame buffer. The decoder can run on any modern microprocessor unit without the CPU loading significantly. The audio receiver loops reading data from the network and queuues the data for output to the speaker. In the event of audio packet loss, the audio receiver preferably ramps the audio level down to silence level and then back up to the nominal audio level of the next successfully received audio packet. The system performs media synchronization to align the audio and video streams at the destination, using techniques such as described by J. D. Northcutt and E. M. Kuerner, "System Support for Time-Critical applications," Proc. NOSSDAV' 91, Germany, pp 242-254.
End-to-end feedback is used in the on demand case to control the flow. In the multicast case, the destinations are slaved to the flow from the server with no feedback. The user interface agent serves as the control connection to the session agent on the media server passing flow control feedback as well as the user's start/stop controls. The user can specify the cost he or she is willing to pay and an appropriate stream will be provided by the system.
A prototype system according to the present invention uses a video data rate that varies from 19.2 kbps to 2 Mbps depending on the spatial and temporal requirement of the decoder and the network bandwidth available. The PSNR varies between 31.63 dB to 37.5 dB. Table 1 gives the results for the decoding of a 160×120 resolution video on a SparcStation 20. It can be seen from Table 1 that the time required to get the highest quality stream (8-bit index) at 160×120 resolution is 2.45 ms per frame (sum of lookup and packing time). This corresponds to a potential frame rate of 400 frames/sec.
TABLE 1______________________________________RESULTS FOR 160 × 120 RESOLUTION (DECODER)No. of Bandwidth as aBits function ofof frame rate (N) CPU time per Packing timeLookup PSNR (dB) Kbps frame (ms) per frame (ms)______________________________________4 31.63 dB 19.2N 1.24 ms 0 ms5 32.50 dB 24N 1.32 ms 0.52 ms6 34 dB 28.8N 1.26 ms 0.80 ms7 35.8 dB 33.6N 1.10 ms 1.09 ms8 31.2 dB 38.4N 1.18 ms 1.27 ms______________________________________
Similarly, Table 2 gives the results for the decoding of a 320×240 resolution video on a SparcStation 20. It can be seen from Table 2 that the time required to get the highest quality stream (8-bit base index and 8-bit first enhancement layer index) at 320×240 resolution is 7.76 ms per frame (sum of look-up and packing time). This corresponds to a potential frame rate of 130 frames/sec.
TABLE 2______________________________________RESULTS FOR 320 × 240 RESOLUTION(8 BIT-LOOKUP BASE)No. of Bandwidth as aBits function ofof frame rate (N) CPU time per Packing timeLookup PSNR (dB) Kbps frame (ms) per frame (ms)______________________________________2 33.72 dB 48N 6.01 ms 0.385 ms4 35.0 dB 52.8N 6.04 ms 0.645 ms5 35.65 dB 62.4N 6.05 ms 0.92 ms6 36.26 dB 67.2N 6.08 ms 1.20 ms7 36.9 dB 72N 6.04 ms 1.48 ms8 37.5 dB 76.8N 6.09 ms 1.67 ms______________________________________
Table 3 gives the results for the decoding of a 640×480 resolution video again on a SparcStation 20. It can be seen from Table 3 that the time required to get the highest quality stream (8-bit base and 8-bit enhancement layer) at 640×480 resolution is 24.62 ms per frame (sum of lookup and packing time). This corresponds to a potential frame rate of 40 frames/sec.
TABLE 3______________________________________RESULTS FOR 640 × 480 WITH 320 × 240 INTERPOLATEDNo. of Bandwidth as aBits function ofof frame rate (N) CPU time per Packing timeLookup PSNR (dB) Kbps frame (ms) per frame (ms)______________________________________2 33.2 dB 48N 22.8 ms 0.385 ms4 34 dB 52.8N 22.87 ms 0.645 ms5 34.34 dB 62.4N 23.14 ms 0.92 ms6 34.71 dB 67.2N 22.93 ms 1.20 ms7 35.07 dB 72N 22.90 ms 1.48 ms8 35.34 dB 76.8N 22.95 ms 1.67 ms______________________________________
Table 4 shows the results for each individual disk for 160×120 resolution video. It can be seen that to get the highest quality stream (8-bit base) at 160×120 requires 5.60 ms of CPU time and an average CPU load of 2% on a SparcStation 20 workstation. The average disk access time per frame is 16 ms.
TABLE 4______________________________________RESULTS FOR 160 × 120 AT THE DISK SERVERNo. of Bandwidth as aBits function ofof frame rate (N) CPU time per Seek-time Avg. CPULookup Kbps frame (ms) (ms) Load______________________________________4 19.2N 2.84 ms 16 ms 1%5 24N 3.67 ms 16 ms 1%6 28.8N 4.48 ms 14 ms 2%7 33.6N 4.92 ms 14 ms 2%8 38.4N 5.60 ms 16 ms 2%______________________________________
Similarly, Table 5 shows the results for each individual disk for 320×240 resolution video. It can be seen that obtaining the highest quality stream (8-bit base and 8-bit enhancement layer) at 320×240 requires 12.73 ms of CPU time and an average CPU load of 7% on a SparcStation 20 workstation. The average disk access time per frame is 18 ms.
TABLE 5______________________________________RESULTS FOR 320 × 240 AT THE DISK SERVERNo. of Bandwidth as aBits function ofof frame rate (N) CPU time per Seek-time Avg. CPULookup Kbps frame (ms) (ms) Load______________________________________2 48N 10.47 ms 18 ms 6%4 52.8N 11.02 ms 16 ms 6%5 62.4N 11.55 ms 18 ms 6%6 67.2N 12.29 ms 20 ms 7%7 72N 12.55 ms 20 ms 7%8 76.8N 12.73 ms 18 ms 7%______________________________________
Modifications and variations may be made to the disclosed embodiments without departing from the subject and spirit of the invention as defined by the following claims.
|Cited Patent
|Filing date
|Publication date
|Feb 28, 1986
|Dec 1, 1987
|Mitsubishi Denki Kabushiki Kaisha
|Interframe adaptive vector quantization encoding apparatus and video encoding transmission apparatus
|Dec 20, 1991
|Dec 1, 1992
|General Electric Company
|Apparatus for segmenting encoded video signal for transmission
|Dec 4, 1991
|Jul 6, 1993
|Intel Corporation
|Adaptive digital video compression system
|Oct 31, 1991
|May 3, 1994
|At&T Bell Laboratories
|Image processing system
|Sep 29, 1993
|Feb 7, 1995
|Anderson; David J.
|Digital audio compression system
|Jun 4, 1992
|Sep 12, 1995
|International Business Machines Corporation
|Sequential pipelined processing for the compression and decompression of image data
|Nov 16, 1994
|Apr 16, 1996
|Massachusetts Institute Of Technology
|Advanced television system
|May 9, 1994
|Jul 2, 1996
|Samsung Electronics Co., Ltd.
|Image compression encoding and decoding method and apparatus therefor
|Citing Patent
|Filing date
|Publication date
|Jul 22, 1997
|Dec 21, 1999
|C-Cube Microsystems, Inc.
|Multiple resolution video compression
|Nov 15, 1996
|Mar 28, 2000
|Matsushita Electric Industrial Co., Ltd.
|Prediction apparatus and method for improving coding efficiency in scalable video coding
|Apr 30, 1997
|Nov 28, 2000
|Ati Technologies
|Method and apparatus for decompression of a two dimensional video texture map
|Oct 19, 1999
|May 8, 2001
|C-Cube Semiconductor Ii, Inc.
|Multiple resolution video compression
|Feb 10, 1997
|Jun 5, 2001
|Kokusai Denshin Denwa Kabushiki Kaisha
|Apparatus for decoding coded video data with reduced memory size
|Nov 16, 1998
|Jun 19, 2001
|Winbond Electronics, Corp.
|Video encounter having an integrated scaling mechanism
|Jul 6, 1999
|Jul 17, 2001
|Philips Electronics North America Corp.
|System and method for fine granular scalable video with selective quality enhancement
|Jul 6, 1998
|Sep 18, 2001
|U.S. Philips Corporation
|Scalable video coding system
|Jan 28, 1999
|Nov 13, 2001
|International Business Machines Corporation
|System for creating multiple scaled videos from encoded video sources
|Jan 8, 1999
|Mar 26, 2002
|Intel Corporation
|Method and apparatus for increasing the effective bandwidth of video sequences transmitted over a network by using cached data
|Jul 6, 1999
|Dec 31, 2002
|Koninklijke Phillips Electronics N.V.
|System and method for improved fine granular scalable video using base layer coding information
|Sep 30, 1997
|Feb 11, 2003
|Sony Corporation
|Encoder, decoder, recording medium, encoding method, and decoding method
|Aug 6, 1999
|Aug 26, 2003
|Nokia Mobile Phones Limited
|Method and apparatus for controlling encoding of a digital video signal according to monitored parameters of a radio frequency communication signal
|Jun 9, 2000
|Oct 28, 2003
|Koninklijke Philips Electronics N.V.
|Hybrid temporal-SNR fine granular scalability video coding
|Jun 30, 2000
|Nov 11, 2003
|Microsoft Corporation
|System and method for selecting the transmission bandwidth of a data stream sent to a client based on personal attributes of the client's user
|Nov 17, 1999
|Jan 27, 2004
|S3 Graphics Co., Ltd.
|Fixed-rate block-based image compression with inferred pixel values
|Jun 23, 1999
|Mar 23, 2004
|University Of Pittsburgh - Of The Commonwealth System Of Higher Education
|Methods and apparatus for dynamic transfer of image data
|Jan 17, 2002
|Aug 10, 2004
|S3 Graphics Co., Ltd.
|Fixed-rate block-based image compression with inferred pixel values
|Nov 7, 2000
|Nov 2, 2004
|Lucent Technologies Inc.
|Methods and apparatus for watermarking maps and other structured data
|Oct 11, 2001
|Dec 28, 2004
|Koninklijke Philips Electronics N.V.
|Spatial scalability for fine granular video encoding
|Mar 6, 2001
|May 31, 2005
|Mitel Networks Corporation
|Sub-packet insertion for packet loss compensation in voice over IP networks
|May 4, 2002
|Aug 2, 2005
|Stentor, Inc.
|Methods and apparatus for partitioning transform data
|Jul 16, 2004
|May 2, 2006
|S3 Graphics Co., Ltd.
|Fixed-rate block based image compression
|Jul 16, 2004
|May 9, 2006
|S3 Graphics Co., Ltd.
|Image processing system
|Mar 1, 2000
|Aug 22, 2006
|Koninklijke Philips Electronics N.V.
|Method and apparatus for streaming scalable video
|Jun 6, 2001
|Dec 26, 2006
|Canon Kabushiki Kaisha
|Image transmission apparatus, image transmission system, and communication apparatus
|May 4, 2001
|Feb 27, 2007
|Hewlett-Packard Development Company, L.P.
|Encoding and decoding methods for secure scalable streaming and related systems
|Mar 22, 2004
|Oct 9, 2007
|Koninklijke Philips Electronics N.V.
|Methods and apparatus for dynamic transfer of image data
|Oct 4, 2001
|Mar 25, 2008
|Hewlett-Packard Development Company, L.P.
|Encoding and encrypting devices for secure scalable data streaming
|Nov 16, 2001
|May 20, 2008
|Stmicroelectronics, Ltd.
|Solid state imaging device with dedicated single pixel readout channels and associated methods
|May 28, 2003
|Jun 10, 2008
|Innovation Management Sciences, Llc
|Predictive interpolation of a video signal
|May 28, 2003
|Jul 8, 2008
|Innovation Management Sciences, Llc
|Maintaining a plurality of codebooks related to a video signal
|May 27, 2005
|Mar 17, 2009
|Ati Technologies Ulc
|Block-based image compression method and apparatus
|Mar 25, 2005
|Oct 20, 2009
|Ati Technologies Ulc
|Block-based image compression method and apparatus
|Feb 13, 2004
|Jan 5, 2010
|Ati Technologies Ulc
|Method and apparatus for block based image compression with multiple non-uniform block encodings
|Dec 9, 2005
|Jan 12, 2010
|The Directv Group, Inc.
|Dynamic mapping of broadcast resources
|May 28, 2003
|Feb 2, 2010
|Diego Garrido
|Video interpolation coding
|Jul 10, 2000
|May 4, 2010
|Hitachi, Ltd.
|Multimedia communication terminal
|May 28, 2003
|May 11, 2010
|Diego Garrido
|Classifying image areas of a video signal
|Jan 31, 2006
|Jul 27, 2010
|Ati Technologies Ulc
|Method and apparatus for anti-aliasing using floating point subpixel color values and compression of same
|Jun 21, 2006
|Jul 27, 2010
|Nokia Corporation
|Method and apparatus for controlling encoding of a digital video signal according to monitored parameters of a radio frequency communication signal
|Mar 2, 2006
|Sep 21, 2010
|S3 Graphics Co., Ltd.
|Image CODEC engine
|Oct 29, 2002
|Mar 8, 2011
|Ati Technologies Ulc
|Image analysis for image compression suitability and real-time selection
|Jul 25, 2007
|Sep 20, 2011
|Innovation Management Sciences
|Predictive interpolation of a video signal
|Sep 26, 2003
|Feb 7, 2012
|Ati Technologies Ulc
|Method and apparatus for compression of multi-sampled anti-aliasing color data
|Nov 24, 2004
|Jul 10, 2012
|Dolby Laboratories Licensing Corporation
|Encoding, decoding and representing high dynamic range images
|Apr 17, 2012
|Aug 21, 2012
|Dolby Laboratories Licensing Corporation
|Encoding, decoding, and representing high dynamic range images
|Jun 16, 2009
|Dec 4, 2012
|Ati Technologies Ulc
|Method and apparatus for block based image compression with multiple non-uniform block encodings
|Jun 11, 2010
|Dec 4, 2012
|S3 Graphics Co., Ltd.
|Image codec engine
|Jul 19, 2012
|Dec 18, 2012
|Dolby Laboratories Licensing Corporation
|Encoding, decoding, and representing high dynamic range images
|Sep 16, 2002
|Mar 5, 2013
|Hewlett-Packard Development Company, L.P.
|Signal format that facilitates easy scalability of data streams
|Nov 7, 2005
|May 21, 2013
|Thomson Licensing
|Film grain simulation for normal play and trick mode play for video playback systems
|Oct 20, 2009
|May 21, 2013
|Thomson Licensing
|Film grain simulation method
|Sep 26, 2005
|Jun 25, 2013
|Thomson Licensing
|Low-complexity film grain simulation technique
|Nov 21, 2005
|Jul 9, 2013
|Thomson Licensing
|Methods, apparatus and system for film grain cache splitting for film grain simulation
|Jul 24, 2012
|Jul 23, 2013
|Cbs Interactive, Inc.
|Techniques to provide an enhanced video replay
|Nov 13, 2012
|Aug 13, 2013
|Dolby Laboratories Licensing Corporation
|Encoding, decoding, and representing high dynamic range images
|Jul 31, 2007
|Aug 20, 2013
|Dolby Laboratories Licensing Corporation
|Apparatus and methods for encoding, decoding and representing high dynamic range images
|Sep 16, 2011
|Aug 27, 2013
|Ati Technologies Ulc
|Method and apparatus for block based image compression with multiple non-uniform block encodings
|May 16, 2012
|May 6, 2014
|Neil Young
|Multiple-resolution audio and video systems, methods of production, delivery and uses thereof
|May 11, 2010
|May 27, 2014
|Qualcomm Incorporated
|Power savings in hierarchically coded modulation
|Jan 18, 2012
|Jul 8, 2014
|Ati Technologies Ulc
|Method and apparatus for compression of multi-sampled anti-aliasing color data
|Apr 25, 2001
|Jul 8, 2014
|At&T Intellectual Property I, Lp
|Method and system for transferring content to a networked unit
|Jul 21, 2009
|Aug 5, 2014
|Thomson Licensing
|Methods for error concealment due to enhancement layer packet loss in scalable video coding (SVC) decoding
|Jul 30, 2013
|Aug 19, 2014
|Ati Technologies Ulc
|Method and apparatus for block based image compression with multiple non-uniform block encodings
|Mar 24, 2014
|Sep 23, 2014
|Neil Young
|Multiple resolution audio and video systems, methods of production, delivery and uses thereof
|Jan 22, 2008
|Oct 7, 2014
|At&T Intellectual Property I, Lp
|Method and apparatus for managing video transport
|May 17, 2009
|Oct 28, 2014
|Qualcomm Incorporated
|Power savings in hierarchically coded modulation
|Dec 3, 2012
|Dec 9, 2014
|S3 Graphics Co., Ltd.
|Image codec engine
|Jul 23, 2013
|Dec 30, 2014
|Cbs Interactive, Inc.
|Techniques to provide an enhanced video replay
|Jan 10, 2011
|Feb 17, 2015
|Nikon Corporation
|Image-capturing device
|Jul 10, 2013
|May 19, 2015
|Dolby Laboratories Licensing Corporation
|Encoding, decoding, and representing high dynamic range images
|Oct 26, 2005
|Aug 4, 2015
|Thomson Licensing
|Bit-accurate film grain simulation method based on pre-computed transformed coefficients
|Nov 8, 2005
|Aug 25, 2015
|Thomson Licensing
|Film grain SEI message insertion for bit-accurate simulation in a video system
|Oct 26, 2005
|Nov 3, 2015
|Thomson Licensing
|Film grain simulation method based on pre-computed transform coefficients
|Apr 2, 2015
|Feb 23, 2016
|Dolby Laboratories Licensing Corporation
|Encoding, decoding, and representing high dynamic range images
|Nov 24, 2014
|Jun 7, 2016
|Cbs Interactive, Inc.
|Techniques to provide an enhanced video replay
|Feb 21, 2014
|Jul 12, 2016
|Nikon Corporation
|Focus estimating device, imaging device, and storage medium storing image processing program
|Sep 17, 2014
|Aug 9, 2016
|Dolby Laboratories Licensing Corporation
|Apparatus and methods for encoding, decoding and representing high dynamic range images
|Mar 6, 2001
|Sep 6, 2001
|Mitel Corporation
|Sub-packet insertion for packet loss compensation in voice over IP networks
|Jun 6, 2001
|Oct 11, 2001
|Takayuki Nagashima
|Image transmission apparatus, image transmission system, and communication apparatus
|Oct 11, 2001
|Jun 13, 2002
|Philips Electronics North America Corporation
|Spatial scalability for fine granular video encoding
|Nov 16, 2001
|Aug 22, 2002
|Stmicroelectronics Ltd
|Solid state imaging device
|May 4, 2001
|Nov 7, 2002
|Wee Susie J.
|Encoding and decoding methods for secure scalable streaming and related systems
|Jan 22, 2002
|Nov 14, 2002
|Weiping Li
|Video encoding and decoding techniques and apparatus
|Sep 16, 2002
|Feb 27, 2003
|Wee Susie J.
|Signal format that facilitates easy scalability of data streams
|Oct 4, 2001
|Apr 10, 2003
|Wee Susie J.
|Encoding and encrypting devices for secure scalable data streaming
|Jul 14, 2003
|Jan 15, 2004
|Romi Singh
|System and method for remote supervision and authentication of user activities at communication network workstations
|May 28, 2003
|Jan 29, 2004
|Diego Garrido
|Predictive interpolation of a video signal
|May 28, 2003
|Jan 29, 2004
|Diego Garrido
|Maintaining a plurality of codebooks related to a video signal
|May 28, 2003
|Feb 5, 2004
|Diego Garrido
|Video interpolation coding
|Feb 22, 2002
|Apr 15, 2004
|Koninklijke Philips Electronics N.V.
|Method for streaming fine granular scalability coded video over an IP network
|Oct 29, 2002
|Apr 29, 2004
|David Oldcorn
|Image analysis for image compression suitability and real-time selection
|Jun 26, 2003
|May 13, 2004
|Matti Jokimies
|Method and apparatus for controlling encoding of a digital video signal according to monitored parameters of a radio frequency communication signal
|Mar 22, 2004
|Sep 16, 2004
|Chang Paul Joseph
|Methods and apparatus for dynamic transfer of image data
|Feb 13, 2004
|Nov 18, 2004
|Konstantine Iourcha
|Method and apparatus for block based image compression with multiple non-uniform block encodings
|Jul 16, 2004
|Dec 23, 2004
|Zhou Hong
|Fixed-rate block based image compression
|Jul 2, 2004
|Feb 3, 2005
|Celartem Technology, Inc.
|Image sharpening with region edge sharpness correction
|Jul 15, 2004
|Jan 19, 2006
|Kimberty-Clark Worldwide, Inc.
|Binders curable at room temperature with low blocking
|Dec 9, 2005
|Apr 27, 2006
|Arsenault Robert G
|Dynamic mapping of broadcast resources
|Nov 7, 2005
|May 18, 2006
|Joan Llach
|Film grain simulation for normal play and trick mode play for video playback systems
|Nov 21, 2005
|Jun 1, 2006
|Cooper Jeffrey A
|Methods, apparatus and system for film grain cache splitting for film grain simulation
|Mar 2, 2006
|Sep 21, 2006
|Zhou Hong
|Image CODEC engine
|Mar 25, 2005
|Sep 28, 2006
|Ati Technologies, Inc.
|Block-based image compression method and apparatus
|May 27, 2005
|Nov 30, 2006
|Ati-Technologies, Inc.
|Block-based image compression method and apparatus
|Feb 14, 2006
|Mar 15, 2007
|Plotky Jon S
|Bandwidth utilization for video mail
|May 28, 2003
|Oct 4, 2007
|Diego Garrido
|Classifying image areas of a video signal
|Oct 11, 2007
|Apr 24, 2008
|Godwin John P
|Device and method for efficient delivery of redundant national television signals
|Sep 26, 2005
|Jun 26, 2008
|Cristina Gomila
|Low-Complexity Film Grain Simulation Technique
|Nov 24, 2004
|Aug 14, 2008
|Brightside Technologies Inc.
|Encoding, Decoding and Representing High Dynamic Range Images
|Jun 6, 2008
|Oct 23, 2008
|Medialive, A Corporation Of France
|Video interfacing and distribution system and method for delivering video programs
|Jul 31, 2007
|Dec 18, 2008
|Brightside Technologies Inc.
|Apparatus and methods for encoding, decoding and representing high dynamic range images
|Oct 11, 2007
|Apr 16, 2009
|Oracle International Corporation
|Reference partitioned tables
|Jun 9, 2008
|Jun 11, 2009
|Samsung Electronics Co., Ltd.
|Method, medium and apparatus encoding/decoding image hierarchically
|Jan 22, 2008
|Jul 23, 2009
|At&T Knowledge Ventures, L.P.
|Method and apparatus for managing video transport
|Jun 16, 2009
|Nov 5, 2009
|Advanced Micro Devices, Inc.
|Method and apparatus for block based image compression with multiple non-uniform block encodings
|May 17, 2009
|Dec 24, 2009
|Qualcomm Incorporated
|Power savings in hierarchically coded modulation
|Oct 20, 2009
|Apr 1, 2010
|Thomson Licensing
|Film grain simulation method
|May 11, 2010
|Sep 2, 2010
|Qualcomm Incorporated
|Power savings in hierarchically coded modulation
|Jun 11, 2010
|Jan 6, 2011
|Via Technologies, Inc.
|Image codec engine
|Jul 21, 2009
|May 26, 2011
|John Qiang Li
|Methods for error concealment due to enhancement layer packet loss in scalable video coding (svc) decoding
|Jan 10, 2011
|Aug 18, 2011
|Nikon Corporation
|Image-capturing device
|May 16, 2012
|May 23, 2013
|Neil Young
|Multiple-Resolution Audio and Video Systems, Methods of Production, Delivery and Uses Thereof
|Jul 23, 2013
|Jan 30, 2014
|Cbs Interactive Inc.
|Techniques to provide an enhanced video replay
|Sep 13, 2013
|Apr 3, 2014
|Microsoft Corporation
|Frame packing and unpacking higher-resolution chroma sampling formats
|Sep 13, 2013
|Apr 24, 2014
|Microsoft Corporation
|Band separation filtering / inverse filtering for frame packing / unpacking higher-resolution chroma sampling formats
|Mar 24, 2014
|Jul 24, 2014
|Neil Young
|Multiple Resolution Audio and Video Systems, Methods of Production, Delivery and Uses Thereof
|Sep 17, 2014
|Jan 1, 2015
|Dolby Laboratories Licensing Corporation
|Apparatus and Methods for Encoding, Decoding and Representing High Dynamic Range Images
|Nov 24, 2014
|Mar 19, 2015
|Cbs Interactive Inc.
|Techniques to provide an enhanced video replay
|Aug 4, 2016
|Nov 24, 2016
|Dolby Laboratories Licensing Corporation
|Apparatus and Methods for Encoding, Decoding and Representing High Dynamic Range Images
|Mar 29, 2007
|Feb 11, 2009
|Method for enhancing medical image with multi-scale self-adaptive contrast change
|Aug 6, 2001
|Feb 14, 2002
|Diva Systems Corporation
|Multiple content supplier video asset scheduling
|Dec 20, 2001
|Jun 27, 2002
|Thomson Licensing S.A.
|Delivering video over an atm/dsl network using a multi-layered video coding system
|Feb 15, 2002
|Nov 7, 2002
|Sbc Technology Resources, Inc.
|Method and system for transferring content to a networked unit
|May 28, 2003
|Dec 11, 2003
|Pixonics, Inc.
|Maintaining a plurality of codebooks related to a video signal
|Jul 21, 2009
|Jan 28, 2010
|Thomson Licensing
|Methods for error concealment due to enhancement layer packet loss in scalable video coding (svc) decoding
|U.S. Classification
|International Classification
|Cooperative Classification
|European Classification
|Jul 5, 1995
Owner name: SUN MICROSYSTEMS, INC., CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:CHADDHA, NAVIN;REEL/FRAME:007537/0308
Effective date: 19950530
|Oct 16, 2001
|Fee payment
Year of fee payment: 4
|Sep 23, 2005
|Fee payment
Year of fee payment: 8
|Sep 23, 2009
|Fee payment
Year of fee payment: 12


text: Computers for NGO's Archive 17/07/2015 An inside view to CSR Corporate Social Responsibility or CSR is a management concept whereby companies integrate social and environmental concerns in their business operations and interactions with their stakeholders. A strategic approach to CSR is increasingly important to by admin | Computers for NGO's Read More 15/07/2015 Digital India Across the length and breadth of this country, India faces many challenges. But when tackled with innovation that leverages the power of technology, it can help create a transformed and digitally empowered India. We by admin | Budget Computers for Education Read More 24/07/2014 How to Reduce Carbon Footprint-The Computing Way! Reducing the carbon footprints becomes absolutely essential for every responsible citizen. This will not only let you enjoy a greener and better environment, but will also buck up the lifespan of your PC. So, by admin | Computers for NGO's Read More 5/07/2014 Computer for everyone – Need of every economy. The relationship between technology and economy has been a subject of debate for centuries. In the earlier times, technology was only the domain of upper class intellectuals. The access to technological advancements was restricted by admin | Computers for NGO's Read More 28/06/2014 Role of NGO in India's poverty alleviation. Poverty has been a firm and importunate problem in India, all the way through the independence to decades after that.Role of NGO, especially in a country like India, is very crucial. In fact, according by admin | Budget Computers for Education Read More 25/06/2014 PC Penetration in India – Why lagging behind? Throughout the last few years, rural India witnessed many extraordinary changes. PC penetration is one such welcome addition which actually improved the lives and the lifestyle of many rural inhabitants. In fact, a series by admin | Computers for NGO's Read More 4/06/2014 Used Computers – How NGOs benefit from it? Throughout the last few years, used computers have played an extremely vital role for the NGOs across the world. These computers are not only handy, but are also extremely purposeful for propagating the various by admin | Computers for NGO's Read More

subset: commoncrawl


text:
The Scavenger Hunt
The Scavenger Hunt
"Oh, Bella!" Alice trilled. Uh-oh. I knew that tone. Whenever Alice used that tone, it only meant one thing. We were going shopping.
"Yes Alice?" I replied warily.
"Come down here, please!" I was up in Edward's room looking through his CDs. I picked myself up and trudged downstairs. Jasper, Rosalie, and Emmett were on the couch and Edward was sitting on the arm of the couch. Alice was bouncing up and down excitedly at the bottom of the stairs.
"Guess what Bella?!" she said.
"What?" I replied, waiting for her to give me the dreadful news.
"We're going on a scavenger hunt!! At the mall!!" Alice said that like she had just won a million dollar shopping spree. I ran over to Edward and clung to him.
"Don't make me go!!" I cried. Edward looked at me helplessly.
"No can do love. She's making us all go." I felt a teensy bit better knowing Edward was coming.
"Well Alice, since I have no choice, could you please explain?" I asked, knowing we were in for a long speech.
"Ok, well we will split up into two teams. Team Butterfly will be Emmett, Bella, and Edward."
"Omigosh, I love butterflies!!" Emmett interrupted. Rosalie promptly smacked his head. "Ow!! Sorry Alice." Emmett said, rubbing his head.
"That's ok Emmett. As I was saying, Team Butterfly will be Emmett, Bella, and Edward. Team Marshmallow will be Jasper, Rosalie, and I." I looked at Edward questioningly. He could tell by the look on my face that I was wondering about the team names. He shrugged and rolled his eyes.
"The rules of the scavenger hunt are as followed: Each item(s) is worth a certain number of points. Whoever has the most points at the end of the two hours wins. However, to qualify you must be at the meeting place when the two hours is up. If not, your team is disqualified. You may not follow the other team around to see where they're going. You must do it on your own. Basically, no cheating Emmett."
"Hey! Why'd you only say my name and not anyone else's?" Emmett whined.
"Because you're the only one that can't be trusted. The team captain will keep track of the points and the items. He or she will also keep track of the 1,000 I'm giving you. The team captain for Team Butterfly is Bella and the team captain of Team Marshmallow is Jasper."
"Why can't Edward be the captain? Or even Emmett?" I pouted. Alice knew I didn't want to do this, so now she's making me captain? Ugh.
"Chill, Bella. I trust you more than I trust Emmett or Edward." Emmett was about to protest but Rosalie flicked him before he got a chance.
"Alright everyone. Here are two envelopes that have the money, the rules, and the items sheet in it. I'm giving you five minutes to look at the items sheet, then we're off!" Alice giggled, then bounced over to Jasper and Rosalie.
"Oh, joy." I mumbled, then I opened up the envelope.
A/N: Hey! Umm I'm having a little trouble posting another chapter. It said to click on "Edit/Upload" on the menu on the left when you login, but I don't know how to do it because there is nothing that says that. Please help me! :D And review:P


text:
Dwyane Wade is a Chicago Bull. Still so shocking.
NBA 2K17 #Friction (Trailer)
A Game 7 for the ages
Steph Curry's Career Mixtape
72-10 Chicago Bulls Mixtape
Bulls Show 154: Bulls Show Back
Jimmy Butler getting Jordan Brand collection
Kobe Bryant x Robert Glasper "Be Courageous" | Nike Basketball
Dell Curry + Stephen Curry Burger King commercial
Chicago Bulls Holiday Scrimmage
Bulls Show 150: Scottie Pippen
NBA's Top 100 Plays of the Season
MJ on LeBron in 1-on-1: "No question."
NBA Stars Music Motivation
The GWHH 2015 NBA Mock Draft
Golden State Warriors 2014-15 NBA Champions
Bulls Show 139: A Mayor Announcement
Bulls Show 137: WTF Bulls
Gowhere NBA Awards: Playoff Edition
Kobe Bryant's Muse (Full Video)
Gowhere NBA Awards: Trade Deadline Edition
Bulls Show 118: A-Town Stomp
Christmas Gowhere NBA Awards
Bulls vs. Warriors: Running Diary
Bulls Show 112: Betting on the Bulls
NBA Extension Fallout
Gowhere NBA Awards (Pt. 2)
Gowhere NBA Awards (Pt. 1)
Bulls 1st Preseason Game Observations
Team USA Takeaways… and its future impact
Our Fan Experience: Team USA vs. Brazil
Bulls Show 91: Divided on Doug
The GWHH 2014 NBA Mock Draft
2014 NBA Champions: San Antonio Spurs
Heat-Spurs II (as told thru song)
Scottie Pippen's Ewing Dunk: 20 Years
A soundtrack for a 1st Round for the ages
S.F. Warriors Stadium no longer on waterfront
The GWHH Definitive Guide to the Post-MJ/Scottie Bulls Postseasons (Pt. 2 of 2)
The GWHH Definitive Guide to the Post-MJ/Scottie Bulls Postseasons (Pt. 1 of 2)
NBA Playoff Preview (told thru songs)
One Shining Moment: UConn Huskies
Steph Curry game winning buzzer beater vs. Mavs
adidas announces Jeremy Lin signing
Bulls Show 68: Special Guest Sgt. Tibs
An annual tradition here as Tibs and his college buddy Jose pick tonight's NBA Draft (and lament a little bit about Derrick Rose.)
Lots of fun fallout from the stunning Cavs victory in Oakland. Congrats, Cleveland!
The NBA's Super Bowl is tonight — one of the biggest, if not THE biggest, game in league history. Get hype with a couple videos inside.
Some great, pre-Game 7 reading. Did you know MJ was 30 minutes away from being a New York Knick?
Found this gem of a hype video, with some Mortal Kombat inspiration, as the perfect watch before Game 1 tonight.
Relive one of T-Mac's career highlights on his birthday.
The trick shot artists outdo not only themselves but the whole world. Including a shot off a 500 ft. skyscraper……….. wow.
Fat Joe reveals the famous Knick that Biggie raps about on ESPN's Highly Questionable.
Plus, watch the unanimous MVP's top 30 plays of this season.
Inspiring life lessons + awesome stories abound in this new Kobe Bryant ESPN feature.
Amazing, comic book style visuals depicting each team's mascot facing off in the first round.


text:
Name: iHubbub
City: Andover
Website: www.ihubbub.com
iHubbub is an online home business network, helping home businesses with client lead generation, helpful advice and networking opportunities.
The iHubbub team all work from home throughout the UK, across Europe and beyond. We realised after running the Remote Worker Awards in 2010 and 2011 that home businesses were crying out for a vibrant community to network with others working from home.
Starting iHubbub at home made financial sense as there was easy access to a cheap office. So we sold up, downsized and moved west to put our passion and energy as well as hard-earned savings into building our home business community.
We use Skype to keep in contact with all of our remote team and we have larger meetings online. We also run our unique online networking event for our home business members.
Having a home-based team means that we have unlimited access to all the skills we need. We operate flexible working hours so our team can take advantage of the benefits of home working while helping other home businesses to succeed.
This keeps owners and staff less stressed, more productive and much more connected with their other interests. iHubbub is proud of its diverse home business community who use their talents and passions to come up with fascinating business solutions.
Paula Wynne is the director of iHubbub
Find out how you can enter our Small Business Showcase here. All entries that meet the criteria are published online.


text:
Real Housewives Queen Housewife Mug
Get Real Housewives merchandise to show your support for the women who rule their domains, and drink to their confidence from a Real Housewives mug. Claim your monarchy, and enjoy a spot of tea or a shot of coffee in the Queen Housewife mug. The black, ceramic mug has a capacity of 11 ounces, and it's embellished with Queen Housewife lettering topped by a royal tiara.
- Additional Details
- Capacity: 11 oz
- Color: Black
- Made Of: Ceramic CA Proposition 65


text:
When the Pirate Prays
€ 16,49
Bisher € 17,49
Lieferbar innerhalb von 2-3 Tagen
Januar 2013
BeschreibungTexas cowboys Billy Birthday (aka Shortcut) and Wallace F. Fidgle (aka Tapes) are touring Florida to see the lighthouses there. In the midst of a storm, they give a ride to a jogger who turns out to be the governor of Florida. And as soon as they drop him off, he's murdered. Stuck in a hotel on remote Gasparilla Island by the vicious tropical squall, the pair are accused of murder by the Lieutenant Governor, who has them arrested them and begins building a case against them. Meanwhile, Shortcut becomes involved with the lovely ex-nun Mary Lynn, who could well be the killer. Events are complicated by political intrigue and a drunken Florida Trooper. And they all must face a possibly disastrous arson fire at the hotel. The more Shortcut learns about the oddball characters stranded at the Inn, the more he sees that each one had a motive to kill the governor. As the storm lashes the island, the two friends must solve the murder in order to save themselves, avoid the killers, and rescue the kidnapped Mary Lynn from a fate worse than death. An absolutely first-rate mix of crime and comedy!
Untertitel: A Comic Crime Novel. 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Sprache: Englisch.
Verlag: Borgo Press
Erscheinungsdatum: Januar 2013
Seitenanzahl: 284 Seiten
Format: kartoniert


text:
Newhall,Caldy Road. CH48 2HG
Newhall - MOT Test Centre.At motoring.co.uk, you can find all the information you require, including a selection of reviews and user experiences, on Newhall based in .
MOT Test Centres
Other Local MOT Test Centres
D & M Motors (west Kirby) Ltd | Apex Automotive Ltd | Brookes Motor Engineers | Burnetts Garage | Curzon Motor Co Limited | Discount Vw Audi Centre | M B Wirral Limited | Me & Jw Pumford Limited | A1 Autocare Centre | Action Services


text:
It only takes a minute to get started. Fill out our simple sign up form and login to the website.
This step is discretionary but will dramatically multiply your chances of getting noticed by other people on the website. Introduce yourself, your hobbies and upload any nice photographs of yourself.
Use our website's advanced search to locate members who suit your needs. Or just browse through listings and locate singles that you like.
Located someone who could be interesting? Send them a word or two or just a wink and see if anything develops. With a little luck you'll be on your way to discovering that special someone for you.
It'll only take 30 seconds


text:
Join River Tees Rediscovered, the Cleveland Industrial Archaeology Society and Teesside Archives on a lovely riverside walk.
From the people that brought you Dirty Dusting, a brand new musical comedy that will have you dying with laughter!
Starring Crissy Rock (Benidorm and I'm a Celebrity), Frazer Hines (Emmerdale and Doctor Who), Billy Pearce, Leah Bell and Paul Dunn.
One ordinary day in the quiet little town of Olwinskirk a chain of extraordinary events begins to take place bringing the lives of Betty, Albert, Billy and the local undertaker, Tristan de Winter, to an uncomfortable crossroads.
Albert Blunderstone has been hiding abroad after having committed a bank robbery with a small time crook called Nodger Wilson. On the day he flies home to attend a funeral, Albert runs into Betty who used to be married to Nodger and in an attempt to find out what happened to his share of the dosh, he befriends Betty and her current husband Billy Blenkinsopp.
The lives of Betty, Albert, Billy and Tristan de Winter become inextricably linked towards a path that is leading to the Pearly Gates and a disgruntled Angel-in-Waiting named Thelma.
Tickets: £20
Book today: 01642 81 51 81 or online www.middlesbroughtheatre.co.uk
Middlesbrough Theatre has quite a remarkable history. From it's conception in the late 1920's to its opening as the first architect-designed theatre to be built after the Second World War - it is the result of a 27-year dream and the unswerving dedication of theatre lovers in Middlesbrough.
Middlesbrough Theatre has an intimacy that belies its 486 seat capacity. A winning combination that has enabled the theatre to play host to a wide variety of performances from big bands and stand-up comedy to full-scale amateur musicals and Indian dance.
Middlesbrough Theatre continues to serve its community hosting performances from leading actors and renowned companies as well as by providing first class facilities to local amateur operatic and dramatic societies as well as young students from local dance schools and performing arts colleges.
On performance days, we re-open for telephone bookings at 6pm (1 1/2 hours before curtain-up on Sundays) and 3/4 hour before curtain-up for personal callers and stay open until 9pm. 01642 81 51 81
The Theatre can accommodate up to six wheelchairs per performance, one free ticket will be issued for each companion. We regret that access to the bar is via stairs: drinks may be ordered and collected from the ground floor kiosk.
An infra-red system is available for the hard of hearing using discreet headsets, which are available from the box office.
Please let us know your requirements at the time of booking to ensure you have a comfortable visit.


text:
Fuimaono strengthens Huskies
Tue., Aug. 20, 2013, midnight
The one apparent certainty for Washington's defense coming into training camp – its stout starting linebackers – is suddenly unsettled.
And that's a good thing.
Senior Princeton Fuimaono has been as impressive as anyone in UW camp, pushing his way into the starting mix at outside linebacker while pushing sophomore Travis Feeney into a reserve role.
"I'm feeling more comfortable with the defense," Fuimaono said. "I had to come out with a mentality to be physical and just do something to get out there on the field. … I've never felt better."
The Huskies haven't settled on a depth chart for the Aug. 31 season opener against Boise State. UW coach Steve Sarkisian said after Monday's practice that he would meet with his staff later in the evening to try to get a better idea of the two-deep roster before beginning to plan for the Broncos in earnest on Wednesday.
Fuimaono was running regularly with the No. 1 defense last week alongside middle linebacker John Timu and opposite fellow outside 'backer Shaq Thompson, with Feeney mostly with the No. 2 defense.
"Everyone wants to talk about our linebackers and they want to talk about Shaq, Feeney and Timu," Sarkisian said, "but Princeton Fuimaono has played a lot of football for us since his true-freshman year. … He's a guy that's extremely reliable for us. He's can play every one of the three positions, and we don't skip a beat when he steps in there. He's tremendous for us on special teams; he starts on every special teams for us. He's just a valuable guy to have, and that's what you want out of your seniors."
Regardless of who ends up starting, the apparent improvement in the corps' depth is a positive sign for a UW defense that will likely rely more on its reserves this season with the Huskies' shift to a no-huddle offense.


text:
Canadian Homes You Can Buy With A Median Income
Buying a home with a median income can seem like an expensive task.
Statistics Canada's most recent estimate of a median household income is $78,870. With that kind of money, you could spend 25 years setting aside 30 per cent of your earnings to pay for a home just under $600,000.
Or, you could take the money you earn and pay off a house in a single year. But you'd be making a whole different kind of sacrifice.
Real estate portal Point2Homes compiled a list of homes where that's possible. But like any seemingly good deal, there's a catch involved.
This big brick box in Empress, a village about 350 kilometres from Calgary, could use a little work on the inside. It's a historic building with potential for a business to run on the main floor and have a residence on the top one. The inside has mostly been torn apart, so you certainly have your work cut out for you.
This three-bedroom P.E.I. home sits on a large, 1.18-acre lot in Duvar, about 120 kilometres from Charlottetown. And it's a fixer-upper. The basement needs foundation. But if you're willing to buy the home as is, it's there for you.
This 625-sq.-ft., one-bedroom apartment is located in Tahsis, a western Vancouver Island community about 150 kilometres from Campbell River. For just under $20,000, you can own a unit that has river and mountain views and comes with a spacious living room. The building has three common barbecue areas. The home's listing pitches it as a "great getaway for fishing."
Sintaluta. It's a small town about 45 minutes away from Regina. And a "motivated" seller wants you to have a piece of it with this three-bedroom, one-bathroom, 1,000-sq.-ft. home that is being sold in as-is, where-is condition. The listing doesn't come with any photos of the interior and it's being pitched as a project for renovators who can "bring life back" into the home. So you likely have some real grunt work to do.
How about that, an affordable home in a major Canadian city! This 626-sq.-ft., one-bedroom apartment is being pitched by an out-of-town seller who's "looking at liquidating his holdings" in Winnipeg. He owns three units, and one of them is this one, which is currently being rented out to tenants who are paying $675 per month plus hydro. So there's a chance to have someone else pay your mortgage. The unit is also assessed at $79,800, so maybe someday you might be able to sell it for what it's worth, at a significant profit to yourself.
"With a little TLC the opportunities are endless." That's how the ad concludes for this 991-sq.-ft. home in Matheson, which is just over 350 kilometres north of Sudbury. It has an "open concept main floor" and an upstairs big enough to build your own little office. It's being sold as is and there are no interior photos attached to the listing.
A giant, two-bedroom home just over the U.S. border in Maine can be yours, if you're willing to put the work into it. It also comes with a dining room, living room, den and laundry room. And one bathroom.
The listing is as honest as they come: "Bring your ideas and tools, this home is in need of a lot of work." It's an 864-sq.-ft. home located in Canso, a small coastal community about 320 kilometres from Halifax. The kitchen has pretty wooden cabinets and the home, overall, looks a tad outdated but could be quite nice with some love. Not too bad for $16,900.
Travel 270 kilometres away from St. John's and you'll find yourself in Dunfield, where you'll find a 994-sq.-ft., two-bedroom home that could be yours with some renovation. Listings show that some windows are missing on the home, and the interior could use some sprucing up too. But it's priced to sell, so if you know how to use your tools, it might be worth a shot.
Only one of these homes is situated in a major city. And it's not Toronto, Vancouver or Montreal.
Many of them need serious work. And those that don't are located as far as 350 kilometres away from a major city centre, so you may find yourself driving a long way for supplies.
City living certainly isn't for everyone. And for them, there's plenty of opportunity. Like a historic building in small-town Alberta; a 1.18-acre lot in P.E.I.; or a B.C. apartment that could double as a fishing getaway.


text:
LIZZIE ARMITSTEAD grabbed Britain's first medal of the Games with a brilliant
silver in the cycling road race.
And the Yorkshire speedster, 23, could hardly believe it.
She said: "To be the first Olympic medallist at your home Games is something I
cannot get my head round.
"I'm still a bit shellshocked to be honest. I'm overjoyed with silver. It's
more than I could have hoped for. I'm so happy for the people that have
supported me to get to this point."
Less than 24 hours earlier, Mark Cavendish's failure to win a medal in the
men's road race had plunged the country into gloom.
But Armitstead gave the storm clouds of the rain-soaked women's event a silver
lining when she crossed the line in second.
She was pipped by Holland's Marianne Vos in a thrilling finish on The Mall.
Armitstead said: "I felt disappointed for the guys yesterday because the work
they put in really deserved a medal. But we raced the race and it worked
She thanked the thousands of fans lining the route for firing her to glory in
the rain.
She said: "It's the most special thing I've ever experienced in my life.
"It was so crazy and inspiring. It was absolutely amazing. I didn't even feel
my legs, it was just so special."
Armitstead was part of a decisive break by four riders 28 miles from the end
of a compelling race filled with crashes and attacking riding.
The four became three when American Shelley Olds suffered a puncture and
Armitstead turned on to The Mall neck and neck with Vos and Russia's Olga
But Vos, one of the greatest women cyclists of all time, just had too much for
her in the final 200 metres and she finished less than a bike's length
Asked whether she had won the silver or lost the gold, Armitstead said: "I won
the silver. I'm just so happy that I committed to the breakaway.
"If you know about women's cycling, you know that Marianne Vos is the best
rider in the world on most courses."
"I've replayed that sprint 15 times already. My only regret is that I didn't
try to jump her earlier in the sprint.
"Vos is faster than most other girls on the circuit. So I'm really chuffed
with silver."


text:
Sun December 11, 2016 - 7:00 PM
Boca Raton, FL, 2016
777 Glades Rd
Boca Raton, FL
Conducted by Patricia P. Fleitas, FAUs presentation of Handels Messiah features FAU choral students PAST and PRESENT, in collaboration with the Delray Beach Chorale. This event sells out early, so buy your tickets today! University...See More


text:
We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Benros, Michael E. Trabjerg, Betina B. Meier, Sandra Mattheisen, Manuel Mortensen, Preben B. Mors, Ole Børglum, Anders D. Hougaard, David M. Nørgaard-Pedersen, Bent Nordentoft, Merete and Agerbo, Esben 2016. Influence of Polygenic Risk Scores on the Association Between Infections and Schizophrenia. Biological Psychiatry,
Haut, Kristen M. Schvarcz, Ariel Cannon, Tyrone D. and Bearden, Carrie E. 2016. Developmental Psychopathology.
Isobe, Masanori Miyata, Jun Hazama, Masaaki Fukuyama, Hidenao Murai, Toshiya and Takahashi, Hidehiko 2016. Multimodal neuroimaging as a window into the pathological physiology of schizophrenia: Current trends and issues. Neuroscience Research, Vol. 102, p. 29.
Marin, Samantha E. and Saneto, Russell P. 2016. Neuropsychiatric Features in Primary Mitochondrial Disease. Neurologic Clinics, Vol. 34, Issue. 1, p. 247.
Tang, Shibing Xie, Min Cao, Nan and Ding, Sheng 2016. Patient-Specific Induced Pluripotent Stem Cells for Disease Modeling and Phenotypic Drug Discovery. Journal of Medicinal Chemistry, Vol. 59, Issue. 1, p. 2.
Tian, Y. Yang, J. Lei, Y. Zhang, Z. Dai, Z. Chen, X. Lui, F. Zhang, J. and Ling, S. 2016. Neonatal ventral hippocampus lesion changes nuclear restricted protein/brain (NRP/B) expression in hippocampus, cortex and striatum in developmental periods of rats. Neuroscience, Vol. 319, p. 59.
Walker, Elaine F. Ryan, Arthur T. Bridgman Goines, Katrina C. Novacek, Derek M. Goulding, Sandra M. Brasfield, Joy L. Macdonald, Allison and Trotman, Hanan D. 2016. Developmental Psychopathology.
Wang, Houliang Guo, Wenbin Liu, Feng Wang, Guodong Lyu, Hailong Wu, Renrong Chen, Jindong Wang, Shuai Li, Lehua and Zhao, Jingping 2016. Patients with first-episode, drug-naive schizophrenia and subjects at ultra-high risk of psychosis shared increased cerebellar-default mode network connectivity at rest. Scientific Reports, Vol. 6, p. 26124.
2016. Functional Neuromarkers for Psychiatry.
Blockus, Heike and Chédotal, Alain 2015. The Genetics of Neurodevelopmental Disorders.
Duan, Jubao 2015. Path from schizophrenia genomics to biology: gene regulation and perturbation in neurons derived from induced pluripotent stem cells and genome editing. Neuroscience Bulletin, Vol. 31, Issue. 1, p. 113.
Guo, Wenbin Liu, Feng Xiao, Changqing Liu, Jianrong Yu, Miaoyu Zhang, Zhikun Zhang, Jian and Zhao, Jingping 2015. Increased short-range and long-range functional connectivity in first-episode, medication-naive schizophrenia at rest. Schizophrenia Research, Vol. 166, Issue. 1-3, p. 144.
Guo, W. Liu, F. Liu, J. Yu, L. Zhang, J. Zhang, Z. Xiao, C. Zhai, J. and Zhao, J. 2015. Abnormal Causal Connectivity by Structural Deficits in First-Episode, Drug-Naive Schizophrenia at Rest. Schizophrenia Bulletin, Vol. 41, Issue. 1, p. 57.
Guo, Wenbin Liu, Feng Zhang, Zhikun Liu, Guiying Liu, Jianrong Yu, Liuyu Xiao, Changqing and Zhao, Jingping 2015. Increased Cerebellar Functional Connectivity With the Default-Mode Network in Unaffected Siblings of Schizophrenia Patients at Rest. Schizophrenia Bulletin, Vol. 41, Issue. 6, p. 1317.
Guo, Wenbin Liu, Feng Chen, Jindong Wu, Renrong Zhang, Zhikun Yu, Miaoyu Xiao, Changqing and Zhao, Jingping 2015. Resting-state cerebellar-cerebral networks are differently affected in first-episode, drug-naive schizophrenia patients and unaffected siblings. Scientific Reports, Vol. 5, p. 17275.
Littow, Harri Huossa, Ville Karjalainen, Sami Jääskeläinen, Erika Haapea, Marianne Miettunen, Jouko Tervonen, Osmo Isohanni, Matti Nikkinen, Juha Veijola, Juha Murray, Graham and Kiviniemi, Vesa J. 2015. Aberrant Functional Connectivity in the Default Mode and Central Executive Networks in Subjects with Schizophrenia – A Whole-Brain Resting-State ICA Study. Frontiers in Psychiatry, Vol. 6,
Peters, Bart D. and Karlsgodt, Katherine H. 2015. White matter development in the early stages of psychosis. Schizophrenia Research, Vol. 161, Issue. 1, p. 61.
Belinsky, Glenn S. Rich, Matthew T. Sirois, Carissa L. Short, Shaina M. Pedrosa, Erika Lachman, Herbert M. and Antic, Srdjan D. 2014. Patch-clamp recordings and calcium imaging followed by single-cell PCR reveal the developmental profile of 13 genes in iPSC-derived human neurons. Stem Cell Research, Vol. 12, Issue. 1, p. 101.
Guo, Wenbin Xiao, Changqing Liu, Guiying Wooderson, Sarah C. Zhang, Zhikun Zhang, Jian Yu, Liuyu and Liu, Jianrong 2014. Decreased resting-state interhemispheric coordination in first-episode, drug-naive paranoid schizophrenia. Progress in Neuro-Psychopharmacology and Biological Psychiatry, Vol. 48, p. 14.
Jalbrzikowski, Maria Villalon-Reina, Julio E. Karlsgodt, Katherine H. Senturk, Damla Chow, Carolyn Thompson, Paul M. and Bearden, Carrie E. 2014. Altered white matter microstructure is associated with social cognition and psychotic symptoms in 22q11.2 microdeletion syndrome. Frontiers in Behavioral Neuroscience, Vol. 8,
Schizophrenia has been thought of as a disorder of reduced functional and structural connectivity. Recent advances in neuroimaging techniques such as functional magnetic resonance imaging, structural magnetic resonance imaging, diffusion tensor imaging, and small animal imaging have advanced our ability to investigate this hypothesis. Moreover, the power of longitudinal designs possible with these noninvasive techniques enable the study of not just how connectivity is disrupted in schizophrenia, but when this disruption emerges during development. This article reviews genetic and neurodevelopmental influences on structural and functional connectivity in human populations with or at risk for schizophrenia and in animal models of the disorder. We conclude that the weight of evidence across these diverse lines of inquiry points to a developmental disruption of neural connectivity in schizophrenia and that this disrupted connectivity likely involves susceptibility genes that affect processes involved in establishing intra- and interregional connectivity.
This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.
Email your librarian or administrator to recommend adding this journal to your organisation's collection.
Full text views reflects the number of PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.
Abstract views reflect the number of visits to the article landing page.
* Views captured on Cambridge Core between September 2016 - 25th May 2017. This data will be updated every 24 hours.


text:
Christina M Maldonado Photographer
RemonstaModel Male Daytona Beach, Florida, US
My MM URL: http://www.modelmayhem.com/remonsta
Mayhem # 2912317
About Me++++++++++++I'm working on both sides of the camera these days. www.Remonsta-Vision.com will be launching in April 2014.+++++++++++++++++++
I'm Nigerian, Blackfoot Native American, and Afro American. Most of my background comes from music. I do hip hop, alternative, and country mainly, but I've dabbled in all genres. I'm a professionally trained stage performer. Modeling is something I've fallen into through promotional work I've done for various musical projects.
New York, Florida, Georgia, North and South Carolina are locations that I frequent so shooting in any of these areas is virtually hassle-free.
Have you worked with Remonsta? Add Credits for Remonsta! >>
Christina M Maldonado Photographer
Ivy Lee Model
Savage R0yal Model
Amelia Simone Model
Gia NYC Model
HeatherVes... Model
Loading Content