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A face detection and/or detection method includes acquiring a digital color image. An active appearance model (AAM) is applied including an interchannel-decorrelated color space. One or more parameters of the model are matched to the image. Face detection results based on the matching and/or different results incorporating the face detection result are communicated.
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This application claims priority to United States provisional patent application no. 60/804,546, filed Jun. 12, 2006, entitled "Improved Colour Model for Face Detection and Tracking" which is hereby incorporated by reference.
The active appearance model (AAM) techniques were first described by Edwards et al. [1]. They have been extensively used in applications such as face tracking and analysis and interpretation of medical images.
Different derivations of the standard AAM techniques have been proposed for grayscale images in order to improve the convergence accuracy or speed. Cootes et al. proposed in [2] a weighted edge representation of the image structure, claiming a more reliable and accurate fitting than using the standard representation based on normalized intensities. Other derivations include the direct appearance models (DAMs) [3], or the Shape AAMs [4], where the convergence speed is increased by reducing the number of parameters that need to be optimized. In the DAM approach, it is shown that predicting shape directly from texture can be possible when the two are sufficiently correlated. The Shape AAMs use the image residuals for driving the pose and shape parameters only, while the texture parameters are directly estimated by fitting to the current texture.
In [5], a method which uses canonical correlation analysis (CCAAAM) for reducing the dimensionality of the original data instead of the common principal components analysis (PCA) is introduced. This method is claimed to be faster than the standard approach while recording almost equal final accuracy.
An inverse compositional approach is proposed in [6], where the texture warp is composed of incremental warps, instead of using the additive update of the parameters. This method considers shape and texture separately and is shown to increase the AAM fitting efficiency.
Originally designed for grayscale images, AAMs have been later extended to color images. Edwards et al. [7] first proposed a color AAM based on the RGB color space. This approach involves constructing a color texture vector by merging concatenated values of each color channel. However, their results did not indicate that benefits in accuracy could be achieved from the additional chromaticity data which were made available. Furthermore, the extra computation required to process these data suggested that color-based AAMs could not provide useful improvements over conventional grayscale AAMs.
Stegmann et al. [8] proposed a value, hue, edge map (VHE) representation of image structure. They used a transformation to HSV (hue, saturation, and value) color space from where they retained only the hue and value (intensity) components. They added to these an edge map component, obtained using numeric differential operators. A color texture vector was created as in [7], using instead of R, G, and B components the V, H, and E components. In their experiments they compared the convergence accuracy of the VHE model with the grayscale and RGB implementations. Here they obtained unexpected results indicating that the RGB model (as proposed in [7]) was slightly less accurate than the grayscale model. The VHE model outperformed both grayscale and RGB models but only by a modest amount; yet some applicability for the case of directional lighting changes was shown.
A method of detecting and/or tracking faces in a digital image is provided. The method includes acquiring a digital color image. An active appearance model (AAM) is applied including an interchannel-decorrelated color space. One or more parameters of the model are matched to the image. A face detection result based on the matching and/or a different processing result incorporating the face detection result is communicated.
The method may include converting RGB data to I1I2I3 color space. The converting may include linear conversion. Texture may be represented with the I1I2I3 color space. The texture may be aligned on separate channels. Operations may be performed on the texture data on each channel separately. The interchannel-decorrleated color space may include at least three channels including a luminance channel and two chromatic channels.
The AAM may include an application of principal components analysis (PCA) which may include eigen-analysis of dispersions of shape, texture and appearance. The AAM may further include an application of generalized procrustes analysis (GPA) including aligning shapes, a model of shape variability including an application of PCA on a set of shape vectors, a normalization of objects within the image with respect to shape and/or generation of a texture model including sampling intensity information from each shape-free image to form a set of texture vectors. The generation of the texture model may include normalization of the set of texture vectors and application of PCA on the normalized texture vectors. The applying may include retaining only the first one or two of the aligned texture vectors. The AAM may also include generation of a combined appearance model including a combined vector from weighted shape parameters concatenated to texture parameters, and application of PCA to the combined vector.
The matching may include a regression approach and/or finding model parameters and/or pose parameters which may include translation, scale and/or rotation.
The interchannel-decorrelated color space may include an orthogonal color space. Effects of global lighting and chrominance variations may be reduced with the AAM. One or more detected faces may be tracked through a series of two of more images.
An apparatus for detecting faces in a digital image is also provided including a processor and one or more processor-readable media for programming the processor to control the apparatus to perform any of the methods described herein.
A more appropriate extension of active appearance modeling (AAM) techniques to color images is provided. Accordingly, the embodiments are drawn to color spaces other than RGB because intensity and chromaticity information are strongly mixed in each of the R, G and B color channels. By employing color spaces where there is a stronger separation of the chromaticity and intensity information, we have been able to distinguish between intensity-dependent and chromaticity-dependent aspects of a color AAM. This has enabled the development of a new approach for normalizing color texture vectors, performing a set of independent normalizations on the texture subvectors corresponding to each color channel. This approach has enabled the creation of more accurate AAM color models than the conventional grayscale model. An investigation across a number of color spaces indicates that the best performing models are those created in a color space where the three color channels are optimally decorrelated. A performance comparison across the studied color spaces supports these conclusions.
The basic AAM algorithm for grayscale images is briefly described below. Then, extension of this model to RGB color images is analyzed, and a CIELAB-based model is proposed. CIELAB is a perceptually uniform color space that is widely used for advanced image processing applications. Extending the AAMs by applying the texture normalization separately to each component of the color space is also analyzed. The 111213 color space, which exhibits substantially optimal decorrelation between the color channels, is shown to be suited to this purpose. The proposed color AAM extension, which realizes a more appropriate texture normalization for color images is also described. Experimental results are shown, and a detailed set of comparisons between the standard grayscale model, the common RGB extension, and our proposed models are provided. Finally, conclusions are presented.
In what follows we frequently use the term texture. In the context of this work, texture is defined as the set of pixel intensities across an object, also subsequent to a suitable normalization.
Overview of the Basic (Grayscale) AAM
The image properties modeled by AAMs are shape and texture. The parameters of the model are estimated from an initial scene and subsequently used for synthesizing a parametric object image. In order to build a statistical model of the appearance of an object a training dataset is used to create (i) a shape model, (ii) a texture model and then (iii) a combined model of appearance by means of PCA, that is an eigenanalysis of the distributions of shape, texture and appearance. The training dataset contains object images, or image examples, annotated with a fixed set of landmark points. These are the training examples. The sets of 2D coordinates of the landmark points define the shapes inside the image frame. These shapes are aligned using the generalized Procrustes analysis (GPA) [9], a technique for removing the differences in translation, rotation and scale between the training set of shapes. This technique defines the shapes in the normalized frame. These aligned shapes are also called the shape examples.
Let N be the number of training examples. Each shape example is represented as a vector s of concatenated coordinates of its points (x1, x2, . . . , xL, y1, y2, . . . , yL)T, where L is the number of landmark points. PCA is then applied to the set of aligned shape vectors reducing the initial dimensionality of the data. Shape variability is then linearly modeled as a base (mean) shape plus a linear combination of shape eigenvectors.
where sm represents a modeled shape, is the mean of the aligned shapes, Φs=((φs1|φs2| . . . |φsp) is a matrix having p shape eigenvectors as its columns (p<N ), and finally, bs defines the set of parameters of the shape model. p is chosen so that a certain percentage of the total variance of the data is retained. The corresponding texture model is next constructed. For that, a reference shape is needed in order to acquire a set of so-called texture examples. The reference shape is usually chosen as the point-wise mean of the shape examples. The texture examples are defined in the normalized frame of the reference shape. Each image example is then warped (distorted) such that the points that define its attached shape (used as control points) match the reference shape; this is usually realized by means of a fast triangulation algorithm. Thus, the texture across each image object is mapped into its shape-normalized representation. All shape differences between the image examples are now removed. The resulting images are also called the image examples in the normalized frame. For each of these images, the corresponding pixel values across their common shape are scanned to form the texture vectors tim=(tim1, tim2, . . . , timp)T, where P is the number of texture samples.
Each texture vector tim is further aligned with respect to intensity values, as detailed below, in order to minimize the global lighting variations. This global texture normalization is designed so that each normalized texture vector is aligned as closely as possible to the mean of the normalized texture vectors.
PCA is next applied to the set of normalized vectors, reducing thus the dimensionality of the texture data. The texture model is also a linear model, a texture instance being obtained from a base (mean) texture plus a linear combination of texture eigenvectors. Thus,
Similar to the shape model, tm represents a synthesized (modeled) texture in the normalized texture frame,
A vector c is further formed by concatenating the shape and texture parameters which optimally describe each of the training examples,
Ws is a diagonal matrix of (normally equal) weights, applied in order to correct the differences in units between the shape and texture parameters.
A model for which the concatenated shape and texture parameters c are used to describe the appearance variability is called an independent model of appearance. A more compact model may be obtained by considering that some correlation exists between shape and texture. Thus, a third PCA is applied on the set of vectors c, resulting in a combined model of appearance
cm=φcbc, (3)
where Φc is the matrix of retained eigenvectors and bc represents the set of parameters that provide combined control of shape and texture variations. This reduces the total number of parameters of the appearance model.
During the optimization stage of an AAM (fitting the model to a query image), the parameters to be found are
where gs are the shape 2D position, 2D rotation and scale parameters inside the image frame, and bc are the combined model parameters.
The optimization of the parameters p is realized by minimizing the reconstruction error between the query image and the modeled image. The error is evaluated in the coordinate frame of the model, i.e., in the normalized texture reference frame, rather than in the coordinate frame of the image. This choice enables a fast approximation of a gradient descent optimization algorithm, described below. The difference between the query image and the modeled image is thus given by the difference between the normalized image texture and the normalized synthesized texture,
r(p)=t−tm, (4)
and ∥r(p)∥2 is the reconstruction error, with ∥.∥ marking the Euclidean norm.
A first order Taylor extension of r(p) is given by
θp should be chosen so that to minimize ∥r(p+θP)μ2 It follows that
Normally, the gradient matrix θr/θp should be recomputed at each iteration. Yet, as the error is estimated in a normalized texture frame, this gradient matrix may be considered as fixed. This enables it to be pre-computed from the training dataset. Given a training image, each parameter in p is systematically displaced from its known optimal value retaining the normalized texture differences. The resulted matrices are then averaged over several displacement amounts and over several training images.
The update direction of the model parameters p is then given by
δp=−Rr(p), (7)
is the pseudo-inverse of the determined gradient matrix, which can be pre-computed as part of the training stage. The parameters p continue to be updated iteratively until the error can no longer be reduced and convergence is declared.
The Texture Normalization Stage
As noted also by Batur et al. [10], and confirmed by our experiments, this stage is preferred during the optimization process, providing enhanced chances for predicting a correct update direction of the parameter vector (θp).
Texture normalization is realized by applying to the texture vector tim a scaling α, and an offset β, being thus a linear normalization,
where 1 is the unity matrix.
The values for α and β are chosen to best match the current vector to the mean vector of the normalized data. In practice, the mean normalized texture vector is offset and scaled to have zero-mean and unit-variance. If
is the mean vector of the normalized texture data, let tzm,uv be its zero-mean and unit-variance correspondent. Then, the values for α and β required to normalize a texture vector tim, according to (8), are given by
Obtaining the mean of the normalized data is thus a recursive process. A stable solution can be found by using one texture vector as the first estimate of the mean. Each texture vector is then aligned to zero mean and unit variance mean vector as described in (8)-(10), re-estimating the mean and iteratively repeating these steps until convergence is achieved.
Color AAM Extensions Based on Global ColorTexture Normalization
It is to be expected that using the complete color information will lead to an increased accuracy of AAM fitting. Yet, previous extensions of AAMs to color images showed only modest improvements, if any, in the convergence accuracy of the model. Before investigating this further, we first present the common AAM extension method to color images. We also propose a variant of this method based on a CIELAB color space representation instead of the initial RGB representation.
RGB is by far the most widely used color space in digital images [11]. The extension proposed by Edwards et al. [7] is realized by using an extended texture vector given by
timG1, tim
where Pc is the number of texture samples corresponding to one channel. Let P=3Pc denote now the number of elements of the full color texture vector.
In order to reduce the effects of global lighting variations, the same normalization method as for the grayscale model, described above, is applied on the full color texture vectors,
timRGB→tRGB (12)
The remaining steps of the basic grayscale algorithm remain unchanged.
CIELAB Extension
CIELAB is a device-independent, perceptually linear color space which realizes a separation of color information into an intensity, or luminance component (L) and two chromaticity components (a, b). CIELAB was designed to mimic the human perception of the differences between colors. It is defined in terms of a transformation from CIE XYZ, which is a device-independent color space describing the average human observer. CIE XYZ is thus an intermediate space in the RGB to CIELAB conversion (RGB→XYZ→CIELAB); the detailed conversion steps are given in the Appendix.
The distance between two colors in the CIELAB color space is given by the Euclidean distance,
ΔE={square root over ((ΔL)2+(Δa)2+(Δb)2)} (13)
CIELAB uses thus the same metric as RGB, and a CIELAB model implementation can be designed simply by substituting in (11) the values corresponding to the R, G, and B components with the values corresponding to the L, a, and b components, respectively. The color texture vector is thus built as
Again, the same normalization technique can be applied on the resulted color vectors,
timCIELAB→tCIELAB. (15)
The CIELAB AAM implementation is interesting as it offers the possibility for a more accurate image reconstruction, aimed towards a human observer. The benefits of this can clearly be noticed when the model is built using a specific image database and tested on another database with different image acquisition attributes (e.g. different illumination conditions). Considering that the image is typically represented in the more common RGB color space, the application of the CIELAB model may be realized at the expense of the added computational cost introduced by the conversion to CIELAB representation.
Texture Normalization on Separate Channel Subvectors
When a typical multi-channel image is represented in a conventional color space such as RGB, there are correlations between its channels. Channel decorrelation refers to the reduction of the cross correlation between the components of a color image in a certain color space representation. In particular, the RGB color space presents very high inter-channel correlations. For natural images, the cross-correlation coefficient between B and R channels is ˜0.78, between R and G channels is ˜0.98, and between G and B channels is ˜0.94 [12]. This implies that, in order to process the appearance of a set of pixels in a consistent way, one must process the color channels as a whole and it is not possible to independently analyze or normalize them.
This observation suggest an explanation as to why previous authors [7] obtained poor results being compelled to treat the RGB components as a single entity. Indeed, if one attempts to normalize individual image channels within a highly correlated color space such as RGB, the performance of the resulting model does not improve when compared with a global normalization applied across all image channels. In a preferred embodiment, however, each image channel is individually normalized when it is substantially decorrelated from the other image channels, and thus an improved color AAM is realized.
There are several color spaces which were specifically designed to separate color information into intensity and chromaticity components. However such a separation still does not necessarily guarantee that the image components are strongly decorrelated. There is though a particular color space which is desirable for substantially optimal image channel decorrelation.
A Decorrelated Color Space
An interesting color space is I1I2I3, proposed by Ohta et al. [13], which realizes a statistical minimization of the interchannel correlations (decorrelation of the RGB components) for natural images. The conversion from RGB to I1I2I3 is given by the linear transformation in (16).
Similar to the CIELAB color space, I1 stands as the achromatic (intensity) component, while I2 and I3 are the chromatic components. The numeric transformation from RGB to I1I2I3 enables efficient transformation of datasets between these two color spaces. I1I2I3 was designed as an approximation for the Karhunen Loeve transform (KLT) of the RGB data to be used for region segmentation on color images. The KLT is optimal in terms of energy compaction and mean squared error minimization for a truncated representation. Note that KLT is very similar to PCA. In a geometric interpretation, KLT can be viewed as a rotation of the coordinate system, while for PCA the rotation of the coordinate system is preceded by a shift of the origin to the mean point [14]. By applying KLT to a color image, it creates image basis vectors which are orthogonal, and it thus achieves complete decorrelation of the image channels. As the transformation to 111213 represents a good approximation of the KLT for a large set of natural images, the resulting color channels are almost completely decorrelated. The I1I2I3 color space is thus useful for applying color image processing operations independently to each image channel.
In the previous work of Ohta et al., the discriminating power of 109 linear combinations of R, G, and B were tested on eight different color scenes. The selected linear combinations were gathered such that they could successfully be used for segmenting important (large area) regions of an image, based on a histogram threshold. It was found that 82 of the linear combinations had all positive weights, corresponding mainly to an intensity component which is best approximated by I1. Another 22 showed opposite signs for the weights of R and B, representing the difference between the R and B components which are best approximated by I2. Finally, the remaining 4 linear combinations could be approximated by I3. Thus, it was shown that the I1, I2, and I3 components in (16) are effective for discriminating between different regions and that they are significant in this order [13]. Based on the above figures, the percentage of color features which are well discriminated on the first, second, and third channel is around 76.15%, 20.18%, and 3.67%, respectively.
I1I2I3Based Color AAM
An advantage of this representation is that the texture alignment method used for grayscale models can now be applied independently to each channel. By considering the band subvectors individually, the alignment method described above can be independently applied to each of them as
The color texture vector is then rebuilt using the separately normalized components into the full normalized texture vector,
In this way, the effect of global lighting variation is reduced due to the normalization on the first channel which corresponds to an intensity component. Furthermore, the effect of some global chromaticity variation is reduced due to the normalization operations applied on the other two channels which correspond to the chromatic components. Thus, the AAM search algorithm becomes more robust to variations in lighting levels and color distributions.
This also addresses a further issue with AAMs which is their dependency on the initial training set of images. For example, if an annotated training set is prepared using a digital camera with a color gamut with extra emphasis on "redness" (some manufacturers do customize their cameras according to market requirements), then the RGB-based AAM will perform poorly on images captured with a camera which has a normal color balance. A model, built using multi-channel normalization, is noticeably more tolerant to such variations in image color balance.
During the optimization process, the overall error function ∥r(p)μ2 is replaced by the weighted error function
The set of weights that correspond to each color channel should be chosen so as to best describe the amount of information contained in that particular image channel. Evidently this is dependent on the current color space representation. For the I1I2I3 color space, the percentages of color features found to be well discriminated for each channel were given above. Note that these percentages can also serve as estimates of the amount of information contained in each channel. Thus, they can provide a good choice for weighting the overall error function. The relative weighting of the error function may be used for texture normalization on separate channel sub-vectors.
As remarked also in [8], the common linear normalization applied on concatenated RGB bands as realized in the RGB implementation is less than optimal. An I1I2I3 based model in accordance with certain embodiments herein uses a separate texture normalization method which is, as described below, a more suitable approach for color images.
Moreover, by employing the I1I2I3 color space, a more efficient compaction of the color texture data is achieved. As the texture subvectors corresponding to I1, I2, and I13 channels are significant in the order of 76%, 20%, and 4%, one can retain about 96% of the useful fitting information out of the first two texture sub-vectors only. Thus, a reduced 1112 model can be designed with the performance comparable to a full I1I2I3 model in terms of final convergence accuracy. Combined with the normalization method of separate texture subvectors in accordance with certain embodiments, a reduced I1I2 model is still more accurate than the original RGB model while the computational requirements are reduced by approximately one third.
A detailed discussion of results, summarized in Tables I to VI, now follows.
The performance of several models were analyzed in the color spaces discussed above. Both texture normalization techniques described were tested for face structure modeling. Use was made in tests of the appearance modeling environment FAME [15], modifying and extending it to accommodate the techniques described herein.
The convergence rates of AAMs are not specifically addressed herein. However, this work is envisioned to move towards real-time embodiments in embedded imaging applications.
The performance of the models is presented in terms of their final convergence accuracy. Several measures are used to describe the convergence accuracy of the models and their ability to synthesize the face. These are the point-to-point (PtPt) and point-to-curve (PtCrv) boundary errors, and the texture error. The boundary errors are measured between the exact shape in the image frame (obtained from the ground truth annotations) and the optimized model shape in the image frame. The point-to-point error is given by the Euclidian distance between the two shape vectors of concatenated x and y coordinates of the landmark points. The point-to-curve error is calculated as the Euclidian norm of the vector of distances from each landmark point of the exact shape to the closest point on the associated border of the optimized model shape in the image frame. The mean and standard deviation of PtPt and PtCrv are used to evaluate the boundary errors over a whole set of images. The texture error is computed as the Euclidian distance between the texture vector corresponding to the original image and the synthesized texture vector after texture de-normalization. This error is evaluated inside the CIELAB color space in order to have a qualitative differentiation between the synthesized images which is in accordance with the human perception. This is called the perceptual color texture error (PTE).
Two standard face image databases were used, namely the CMU PIE database [16] and the IMM database [17]. Color images of individuals with full frontal pose, neutral expression, no glasses, and diffuse light were used in these tests. Thus, a set of 66 images (640×486 pixels) was taken from the entire PIE database and a second set of 37 images (640×480 pixels) from the IMM database. These reduced sets of images are referred to below when mentioning the PIE and IMM databases. The images were manually annotated using 65 landmark points as shown in
For the PIE database, the first 40 images were used in building the models. The convergence accuracy was tested on the same set of 40 images, called PIE Subset 1 or seen data, and separately on the remaining 26 images, called PIE Subset 2 or unseen data. The IMM database was similarly split into IMM Subset 1, containing the first 20 images (seen data), and IMM Subset 2 with the remaining 17 images (unseen data). By doing this, how well the models are able to memorize a set of examples was analyzed, and also their capability to generalize to new examples. All models were built so as to retain 95% of the variation both for shape and texture, and again 95% of the combined (appearance) variation. For cross-validation, the PIE models were applied on the full IMM database, as well as the IMM models on the full PIE database.
The following AAM implementations were analyzed:
- standard grayscale model (Grayscale);
- RGB model with global color texture normalization (RGB GN);
and the proposed models,
- CIELAB model with global texture normalization (CIELAB GN);
- I1I2I3 model with texture normalization on separate channel sub-vectors (I1I2I3 SChN);
- I1I2 model with texture normalization on separate channel sub-vectors (I1I2 SChN);
and also the remaining (color space)/(normalization method) possibilities were added to provide a complete comparative analysis,
- RGB model with texture normalization on separate channel sub-vectors (RGB SChN);
- CIELAB model with texture normalization on separate channel sub-vectors (CIELAB SChN);
- I1I2I3 model with global texture normalization (I1I2I3GN);
- I1I2 model with global texture normalization (I1I2 GN).
The grayscale images were obtained from the RGB images by applying the following standard mix of RGB channels,
Grayscale=0.30R+0.59G+0.1 1B. (19)
The testing procedure for each model is as follows: each model is initialized using an offset for the centre of gravity of the shape of 20 pixels on the x coordinate and 10 pixels on the y coordinate from the optimal position in the query image. The optimization algorithm (see above) is applied, and the convergence accuracy is measured. Convergence is declared successful if the point-to-point boundary error is less than 10 pixels.
In order to provide an indication on the relevancy of the chosen (-20,-10) pixels initial displacement, as well as to have an indication on the convergence range differences between the models, convergence accuracy was studied for a wider range of initial displacements on the x coordinate (dx), keeping the −10 pixels displacement on the y coordinate fixed. The tests were performed on PIE Subset 2 (unseen data) and are presented in
From Table I Table VI, the successful convergence rate for the three proposed models is consistently the best in comparison to all other model implementations, being usually much higher than for the grayscale model. An inconclusive result was obtained for IMM database (Table III and Table IV), where most of the studied models converged successfully on all images. Interestingly, it can be noticed that the RGB GN model does not outperform the grayscale model, the successful convergence rate being actually lower for some of the studied cases. In particular, for the cross-validation tests, when applying the PIE models on IMM database (Table V), the RGB GN model has a very poor rate, being actually outperformed by all other model implementations. For the same situation, all three proposed models have very high convergence rates, particularly the I1I2I3 SChN model which registered a rate of 100%. Notable results were also obtained for the case of applying IMM models on PIE database (Table VI).
In terms of convergence accuracy (PtPt, PtCrv) and perceptual texture error, it can be seen that the CIELAB implementation is still dependent to some extent on the image acquisition conditions. This is caused by the limitation of the CIELAB implementation which cannot be efficiently used with texture normalization on separate channel sub-vectors. Some redundancy of RGB coordinates is removed by separating intensity and chromaticity data, yet the components are still coupled during texture normalization. Thus, although the results are improved over the RGB implementation for many of the tested image datasets, especially for the cross-validation tests (Table V and Table VI), they seem to lack consistency (see Table III and Table IV).
Much more consistent results were obtained for I1I2I3 SChN and I1I2 SChN models, where the convergence accuracy is significantly improved over the RGB GN implementation for all studied datasets. For I1I2I3 SChN model the perceptual texture error is also notably reduced for all datasets.
The embodiments described above have been analyzed with respect to how changes in color space representation of an image influence the convergence accuracy of AAMs. In particular, AAMs have been compared that have been built using RGB, CIELAB and I1I2I3 color spaces. Both of the latter color spaces provide a more natural separation of intensity and chromaticity information than RGB. The I1I2I3 color space also enables the application of more suitable color texture normalization and as a consequence model convergence is significantly improved.
From described experiments, it was deduced that it would make sense to normalize each color channel independently, rather than applying a global normalization across all three channels.
Thus, a more natural color texture normalization technique is proposed in certain embodiments, where each texture subvector corresponding to an individual color channel is normalized independently of the other channels. Although this approach cannot be successfully used with the common RGB representation, it was determined that some significant results can be achieved in color spaces where intensity and chromaticity information are better separated. In particular, it was found that the I1I2I3 color space, which was specifically designed to minimize cross-correlation between the color channels, is an advantageously practical choice for this purpose.
Also, applying the same normalization as for grayscale images on an RGB color texture vector can occasionally lead to decreased convergence accuracy, as suggested in earlier research [8]. Thus, there is little rationale to use an RGB based model as the additional color data does not reliably improve model convergence and it will take three times as long to perform matching operations. For these reasons, the common RGB extension of the basic AAM is only interesting for the purpose of rendering the full color information.
Yet, by employing the I1I2I3 color space coupled with texture normalization on separate channel subvectors, significant improvement in convergence accuracy is achieved as well as an accurate reconstruction of the current color image. The reconstruction accuracy, determined by analyzing the mean texture error, is also improved when compared with models based on other color spaces. By using the proposed I1I2I3 model with texture normalization on separate channel subvectors, the optimization algorithm, which is typically based on a gradient descent approximation, is less susceptible to errors caused by local error function minima. Thus, the algorithm performance is also noticeably more robust.
More than 96% of relevant data is encapsulated in the I1 and I2 components of the 111213 color space. The difference between using an AAM derived from a full I1I2I3 color space representation and one which is built by retaining only the first two channels is not very significant. Where the speed of convergence is most important, the reduced I1I2 model might be favored to a full I1I2I3 model due to the lower dimensionality of the overall texture vector and the reduced computational requirements of this two-channel model.
The present invention is not limited to the embodiments described above herein, which may be amended or modified without departing from the scope of the present invention as set forth in the appended claims, and structural and functional equivalents thereof.
In methods that may be performed according to preferred embodiments herein and that may have been described above and/or claimed below, the operations have been described in selected typographical sequences. However, the sequences have been selected and so ordered for typographical convenience and are not intended to imply any particular order for performing the operations.
In addition, all references cited above herein, in addition to the background and summary of the invention sections, as well as US published patent applications nos. 2006/0204110, 2006/0204110, 2006/0098890, 2005/0068446, 2006/0039690, and 2006/0285754, and U.S. patent applications Ser. Nos. 11/464,083, 60/804,546, 11/554,539, 60/829,127, 60/773,714, 60/803,980, 60/821,956, and 60/821,165, which are to be or are assigned to the same assignee, are all hereby incorporated by reference into the detailed description of the preferred embodiments as disclosing alternative embodiments and components.
In addition, the following United States published patent applications are hereby incorporated by reference for all purposes including into the detailed description as disclosing alternative embodiments:
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[5] R. Donner, M. Reiter, G. Langs, P. Peloschek, and H. Bischof, "Fast active appearance model search using canonical correlation analysis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 10, pp. 1690-1694, 2006.
[6] I. Matthews and S. Baker, "Active appearance models revisited," International Journal of Computer Vision, vol. 60, no. 2, pp. 135 - 164, November 2004, in Press.
[7] G. J. Edwards, T. F. Cootes, and C. J. Taylor, "Advances in active appearance models," in International Conference on Computer Vision (ICCV'99), 1999, pp. 137-142.
[8] M. B. Stegmann and R. Larsen, "Multiband modelling of appearance," Image and Vision Computing, vol. 21, no. 1, pp. 61-67, jan 2003. [Online]. Available: http://www2.imm.dtu.dk/pubdb/p.php?1421
[9] C. Goodall, "Procrustes methods in the statistical analysis of shape," Journal of the Royal Statistical Society B, vol. 53, no. 2, pp. 285-339, 1991.
[10] A. U. Batur and M. H. Hayes, "Adaptive active appearance models." IEEE Transactions on Image Processing, vol. 14, no. 11, pp. 1707- 1721, 2005.
[11] G. Sharma and H. J. Trussell, "Digital color imaging," IEEE Transactions on Image Processing, vol. 6, no. 7, pp. 901-932, 1997. [Online]. Available: citeseer.ist.psu.edu/sharma97digital.html
[12] M. Tkal{hacek over ( )}ci{hacek over ( )}c and J. F. Tasi{hacek over ( )}c, "Colour spaces perceptual, historical and applicational background," in IEEE, EUROCON, 2003.
[13] Y. Ohta, T. Kanade, and T. Sakai, "Color information for region segmentation," in Computer Graphics and Image Processing, no. 13, 1980, pp. 222-241.
[14] J. J. Gerbrands, "On the relationships between SVD, KLT and PCA." Pattern Recognition, vol. 14, no. 16, pp. 375-381, 1981.
[15] M. B. Stegmann, B. K. Ersboll, and R. Larsen, "FAME a flexible appearance modelling environment," IEEE Transactions on Medical Imaging, vol. 22, no. 10, pp. 1319-1331, 2003. [Online]. Available: http://www2.imm.dtu.dk/pubdb/p.php?1918
[16] T. Sim, S. Baker, and M. Bsat, "The CMU pose, illumination, and expression (PIE) database of human faces," Robotics Institute, Carnegie Mellon University, Pittsburgh, Pa., Tech. Rep. CMURITRO102, January 2001.
[17] M. M. Nordstrom, M. Larsen, J. Sierakowski, and M. B. Stegmann, "The IMM face database an annotated dataset of 240 face images," Informatics and Mathematical Modelling, Technical University of Denmark, DTU, Richard Petersens Plads, Building 321, DK2800 Kgs. Lyngby, Tech. Rep., may 2004. [Online]. Available: http://www2.imm.dtu.dk/pubdb/p.php?3160
1. A method of detecting faces in a digital image, comprising:
- (a) acquiring a digital color image;
- (b) applying an active appearance model (AAM) including an interchannel-decorrelated color space;
- (c) matching one or more parameters of the model to the image; and
- (d) communicating a face detection result based on the matching or a different processing result incorporating said face detection result, or both.
2. The method of claim 1, further comprising converting RGB data to I1I2I3 color space.
3. The method of claim 2, wherein the converting comprises linear conversion.
4. The method of claim 2, further comprising representing texture with the I1I2I3 color space.
5. The method of claim 4, further comprising aligning the texture on separate channels.
6. The method of claim 4, further comprising performing operations on the texture data on each channel separately.
7. The method of claim 1, wherein said interchannel-decorrleated color space comprises at least three channels including a luminance channel and two chromatic channels.
8. The method of claim 1, wherein the AAM comprises an application of principal components analysis (PCA).
9. The method of claim 8, wherein said PCA comprises eigen-analysis of dispersions of shape, texture and appearance.
10. The method of claim 8, wherein the AAM further comprises an application of generalized procrustes analysis (GPA) including aligning shapes.
11. The method of claim 10, wherein the AAM further comprises a model of shape variability including an application of PCA on a set of shape vectors.
12. The method of claim 11, wherein the AAM further comprises a normalization of objects within the image with respect to shape.
13. The method of claim 12, wherein the AAM further comprises generation of a texture model including sampling intensity information from each shape-free image to form a set of texture vectors.
14. The method of claim 13, wherein the generation of the texture model comprising normalization of the set of texture vectors and application of PCA on the normalized texture vectors.
15. The method of claim 14, wherein the applying comprises retaining only the first one or two of the aligned texture vectors
16. The method of claim 14, wherein the AAM further comprises generation of a combined appearance model including a combined vector from weighted shape parameters concatenated to texture parameters, and application of PCA to the combined vector.
17. The method of claim 1, wherein the matching comprising a regression approach.
18. The method of claim 1, wherein the matching comprises finding model parameters or pose parameters or both.
19. The method of claim 18, wherein the pose parameters comprise translation, scale or rotation, or combinations thereof.
20. The method of claim 1, wherein said interchannel-decorrelated color space comprises an orthogonal color space.
21. The method of claim 1, wherein effects of global lighting and chrominance variations are reduced with said AAM.
22. The method of claim 1, further comprising tracking one or more detected faces through a series of two of more images.
23. An apparatus for detecting faces in a digital image, comprising a processor and one or more processor-readable media for programming the processor to control the apparatus to perform a method comprising:
- (a) acquiring a digital color image;
- (b) applying an active appearance model (AAM) including an interchannel-decorrelated color space;
- (c) matching one or more parameters of the model to the image; and
- (d) communicating a face detection result based on the matching or a different result incorporating said face detection result, or both.
24. The apparatus of claim 23, wherein the method further comprises converting RGB data to I1I2I3 color space.
25. The apparatus of claim 24, wherein the converting comprises linear conversion.
26. The apparatus of claim 24, wherein the method further comprises representing texture with the I1I2I3 color space.
27. The apparatus of claim 26, wherein the method further comprises aligning the texture on separate channels.
28. The apparatus of claim 26, wherein the method further comprises performing operations on the texture data on each channel separately.
29. The apparatus of claim 23, wherein said interchannel-decorrleated color space comprises at least three channels including a luminance channel and two chromatic channels.
30. The apparatus of claim 23, wherein the AAM comprises an application of principal components analysis (PCA).
31. The apparatus of claim 30, wherein said PCA comprises eigen-analysis of dispersions of shape, texture and appearance.
32. The apparatus of claim 30, wherein the AAM further comprises an application of generalized procrustes analysis (GPA) including aligning shapes.
33. The apparatus of claim 32, wherein the AAM further comprises a model of shape variability including an application of PCA on a set of shape vectors.
34. The apparatus of claim 33, wherein the AAM further comprises a normalization of objects within the image with respect to shape.
35. The apparatus of claim 34, wherein the AAM further comprises generation of a texture model including sampling intensity information from each shape-free image to form a set of texture vectors.
36. The apparatus of claim 35, wherein the generation of the texture model comprising normalization of the set of texture vectors and application of PCA on the normalized texture vectors.
37. The apparatus of claim 36, wherein the applying comprises retaining only the first one or two of the aligned texture vectors
38. The apparatus of claim 36, wherein the AAM further comprises generation of a combined appearance model including a combined vector from weighted shape parameters concatenated to texture parameters, and application of PCA to the combined vector.
39. The apparatus of claim 23, wherein the matching comprising a regression approach.
40. The apparatus of claim 23, wherein the matching comprises finding model parameters or pose parameters or both.
41. The apparatus of claim 40, wherein the pose parameters comprise translation, scale or rotation, or combinations thereof.
42. The apparatus of claim 23, wherein said interchannel-decorrelated color space comprises an orthogonal color space.
43. The apparatus of claim 23, wherein effects of global lighting and chrominance variations are reduced with said AAM.
44. The apparatus of claim 23, wherein the method further comprises tracking one or more detected faces through a series of two of more images.
Patent History
Type: Application
Filed: Jun 12, 2007
Publication Date: Jan 17, 2008
Patent Grant number: 7965875
Applicant: FotoNation Vision Limited (Galway City)
Inventors: Mircea Ionita (Galway), Peter Corcoran (Claregalway)
Application Number: 11/761,647
International Classification: G06K 9/00 (20060101);


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The first clue, lesson number one from human history on the subject of nonviolence, is that there is no word for it...while every major language has a word for violence, there is no word to express the idea of nonviolence except that it is not the other idea, it is not violence.
- Mark Kurlansky, Nonviolence - The History of a Dangerous Idea
I went just a teesy weensy bit overboard the other day and jumped down my friend odum's throat for his intro to a post on "just war." But I apologized for my original harangue, and the discussion was extensive and in the end I think fruitful.
What set me off was an implication of passivity in those of us who work for and through nonviolence. That we reject military action in a mechanical, knee jerk fashion, then move on while exploring no alternative solutions to crisis. Mostly I got pissed by his use of the word 'pacifist', which I hate with the heat of ten gajillion quasars, and it was downhill from there.
Now I'm not picking on odum again here, just providing some backstory to my latest blogifesto on nonviolence. I think there is truly a misconception about most people whom you'd call "pacifists", in part perhaps because of the label itself (and others like "passive resistance" which Gandhi coined and later rejected), so I'd like to expand on some things I'd brought up in that thread.
Nonviolence is not simply the lack of violence, but really the refusal to use one tool in favor of another as part of conflict resolution. As Gene Sharp, who catalogued 198 methods of nonviolent action, observes:
Nonviolent action is a technique by which people who reject passivity and submission, and who see struggle as essential, can wage their conflict without violence. Nonviolent action is not an attempt to avoid or ignore conflict. It is one response to the problem of how to act effectively in politics, especially how to wield powers effectively.
The key takeaway is that nonviolence is a weapon used from a position of strength, as opposed to weakness, and requires aggressive action, as opposed to passive inaction. It has been successfully deployed tactically and strategically myriad times, and with each new victory and defeat we learn how to use it more effectively.
Since this approach is not simply avoiding armed conflict, yet still seeks positive outcomes, it is not a one-size-fits-all philosophy and rather recognizes the complexity and uniqueness of each situation. No tool necessarily works in all environments. For example, economic sanctions have forced the issue in South Africa and even Libya, could probably have similar impact in Israel, were disastrous in Iraq and have been largely ineffectual in Burma. So there is no deterministic formula in searching for alternatives to warfare and thus we really need serious R&D in this arena--lots of experimentation has already been done over the last century for us to build upon.
It's a field ripe for study. How can nations defend themselves from invasion nonviolently? How can nonviolence be brought to bear against terrorism? Etc.
This is part of the great value I see in Dennis Kucinich's proposal to establish a Cabinet-levelDepartment of Peace. To some folks--including a friend of mine who ran for US Senate--that might seem redundant. Afterall, don't we already have a State Department that's supposed to do that?
Not really. Diplomacy isn't the be all of nonviolence. In fact, we often use it in the lead up to war not as a way to avoid violent conflict, but as we saw in building a coalition to bomb Libya, as a way to foster it. Even when not getting allies in line for war, State is sorta the good cop to Defense' bad cop--hey, negotiate with me because otherwise that crazy General Mayhem is gonna fuck your shit UP!
The problem is we don't do peace very well. We do absence of war. A Peace Department would at least work to alter our default posture and:
- Proactively develop policies, strategies and recommendations for expanding our capacity for nonviolent conflict resolution and for addressing the root causes to violence, both internationally and domestically
- Promote, fund and expand programs proven effective at reducing and preventing violence
- Strategically coordinate existing efforts within the federal government relating to conflict resolution
- Through the Secretary of Peace, provide a voice at the cabinet-level for nonviolent approaches to both domestic and international crises and conflicts
- Support our military with new peacebuilding capabilities desperately needed in the war on terror
- Establish a U.S. Peace Academy, on par with the U.S. military service academies, to train military and civilian peacekeepers, and ensure the development and application of expert nonviolent resources in conflict resolution
Give the DoP a budget worth, say...112 Tomahawk missiles and I'd say that's a great start. Or 1 month of the war in Afghanistan. Or maybe 1/100th of the DoD budget. Whatever, we can quibble over the exact dollars later.
In any discussion of nonviolence certain questions almost always arise. There's my old favorite, "would you kill somebody if they invaded your home and skullfucked your family?" And then, "how could nonviolence work against Hitler?"
I generally observe there were many, many examples of heroic, tactical examples of nonviolent resistance against the Nazi regime. But since it's all speculative history as a thought experiment, I note that while people did nonviolently fight back in 1943, it's more instructive to consider how people could have done so in 1933 or even 1923.
While nonviolent movements have earned success in a matter of days or weeks, as we saw in the Philippines 25 years ago, as well as in Tunisia and Egypt this year, to be most effective we have to take the long view, both as people-powered movements and state actors. So in the case of Germany, if we better understand the dynamics of crisis and violence, perhaps the victorious Allies would not have imposed such a punitive "peace" on Germany--maybe even anticipate the Marshall Plan a few decades earlier. Or in response to the Ruhrkampf, France could have accepted a more progressive version of the Dawes Plan. Then we don't have things spiral out of control to the point that appeasement substitutes for genuine peace in 1938, paving the path for all out war.
Apply the long view to the Middle East and we can see similar historical inflection points. Don't have the CIA sponsor a coup in 1953 Iran. Don't support the Shah. Don't get blowback in the form of Islamic revolution (which, BTW, was an example of civil resistance). Don't arm Saddam during the Iran-Iraq War. Don't launch a 20 year war against Iraq.
We can also flip this around from a series of Don'ts to more positive Dos. Take Kosovo and Serbia.
Madeleine Albright famously called us "the indisipensable nation." Not in the context of peace, but of diplomacy backed by immense military power that we must be willing to use. She also complained to Colin Powell, "What's the point of having this superb military you're always talking about if we can't use it?"
So her hammer found a nail in the Kosovo War in 1998-99. Would that the United States had proven itself indispensible years earlier when the Kosovo Albanians were using nonviolent methods to secure their autonomy. Would that we had a SecState who complained to SecPeace Kucinich, "What's the point of having these superb Soldiers of Peace you're always talking about if we can't use them?"
Instead we only view ourselves indispensable putting out horrific fires instead of working to prevent them in the first place. Fire departments remind people to change batteries in smoke detectors, teach children how to behave in a house fire and other things to mitigate the need for fire trucks to roll. We need to take a similar approach to the world's conflagrations.
Again, as history is the what it is, I don't know exactly how we might have helped Kosovo without letting the situation devolve into Serbian aggression and NATO military action. I will also note history shows us that in the end NATO's bombs didn't get rid of Milosevic, who instigated things, but the Serbian people's nonviolence did, which this year inspired Tunisian and Egyptian revolutionaries.
Perhaps we can also learn from Otpor and the many other people who have fought for peace, freedom and justice with a powerful weapon. Reorganizing our society around nonviolent principles can start simply by shifting personal attitudes from "that shit'll never work" to "let's think about how it can." Then maybe we'll invent a word that uniquely means nonviolence, and the opposite of that concept will struggle to find definition in our language...
Across town, an even larger number converged on a square chanting slogans calling for his ouster and waving red cards emblazoned with the word "leave" despite fears of more violence a week after government security forces shot dead more than 40 demonstrators in Sanaa.
The bloodshed last Friday prompted a wave of defections by military commanders, ruling party members and others, swelling the ranks of the opposition and leaving the president isolated.
When NV is met with violence, it increases the chances that the people being asked to carry out repression will defect to the opposition. If the resisters turn to violence in response--which is part of the goal of the attacks in the first place--then the regime's actions are more easily justified and the apparatus loses fewer components.

subset: commoncrawl


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If Christmas is overwhelming you, there's nothing quite like a brisk walk to de-stress before the main event; or maybe blow away those festive cobwebs and calories in the fresh air during the holidays afterwards.
Exhaust a few younger family members, and glean a little garden inspiration at the same time, and enjoy the tracery of bare branches, coloured stems and bark, seed heads and structure, as well as exciting sideshows set up to tempt you to one of the gardens open over the holidays, or on the day itself.
KEW GARDENS are opening their doors after dark with an illuminated trail bringing their much-loved landscape to life. During the day, visit their Christmas village, Santa's woodland grotto and market, and walk in the gardens open daily except December 24 and 25. To book, or find out more, see kew.org or call 0208 332 5655, and don't forget their country estate, Wakehurst in West Sussex.
Visit ALNWICK GARDENS in Northumberland at dusk and admire their Sparkle lighting installation, transforming the gardens with light and colour till January 5 (late-night opening till 7pm on Fridays and Saturdays). By day, the garden's living green architectural structure looks at its best at this time of the year. For opening times, see alnwickgarden.com (01663 511350).
THE HIDDEN GARDENS OF HELIGAN in Cornwall will be highlighted with special lantern-lit walks over the holidays, (closed December 24 and 25), with visits from Father Christmas and charity open days on Boxing and New Year's Day. Take a woodland walk and see how the bare branches offer lots of opportunities for birdwatchers, or visit the Hidesmoor wildlife hide. See heligan.com or call 01726 845100.
THE NATIONAL TRUST WADDESDON MANOR near Aylesbury, Bucks, is open between Christmas and the New Year (closed Christmas Eve, Christmas Day and Boxing Day), with woodland playgrounds and a fabulous light installations trail (01296 653226; waddesdon.org.uk for late-night openings). Other Trust Gardens including Scotney Castle, Hardwick Hall, Nymans and Anglesey Abbey have gardens full of winter interest, for further information, visit nationaltrust.org.uk.
TRENTHAM GARDENS near Stoke-on-Trent are open throughout the holiday, apart from Christmas Day itself, and their Italian Garden designed by Tom Stuart-Smith and Piet Oudolf's Rivers of Grass are stunning in winter. Book a skating session on their lakeside rink (trentham.co.uk; 01782 646646).
THE RHS SHOW GARDENS AT WISLEY are always worth a winter visit. Their glasshouses, full of Christmas plants, are open till January 5, and there's an Enchanted Story Trail to amuse the children while you inhale the scented plants in the Rock Gardens (except Christmas Day and New Year's Eve). The RHS's other gardens are open with lots of seasonal interest: Himalayan birches and paper bark maples at Rosemoor in Devon and architectural grasses at Harlow Carr in Yorkshire. See rhs.org.uk.
TRY SOMETHING DIFFERENT: a family Treasure Hunt with sets of clues, quizzes and glorious walks in town or countryside. Pick Hampstead or St Pauls with hidden city gardens in London, the Cotswolds or Cheshire villages, or the North Norfolk Coast or Whitstable by the sea and spend a day exploring your chosen area. Suitable for those over eight years. See treasuredays.com (020 78742 0551).
RICH PICKINGS We'll be walking in the gardens of Belmont House at Throwley near Faversham in Kent. Open every day of the year from 10am till dusk during winter, with plenty of seasonal interest in their walled kitchen garden with variously shaped pruned fruit trees and in the pinetum. See belmont-house.org (01795 890202).


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Will, you are the best for keeping up with all of this! Does Michele still have a job? What's the husband think of all the travel I wonder?Natalie is one sick puppy. I was half way hoping she wouldn't be like this out of the house, but I guess it was her true personality that we saw.
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VIDEO: Brent Barry breaks down the Rockets' recent success in this version of 'Breaking Bones'
HOUSTON — Birds fly. Fish swim.
Daryl Morey trades.
Underneath all the talk of the Rockets adding a wing shooter and perimeter defender at the deadline — they landed Jordan Hamilton from the Nuggets — was a huge, hard-wired part of Morey's DNA that said: Do something. Something big.
Surely, Morey would have leaped at the chance to, say, reel in Rajon Rondo from his old Boston stomping grounds, if Danny Ainge had been so inclined. But the truth was the Rockets never really had the chips to the put onto the table — a premium first round draft choice or two — to even get the Celtics thinking seriously.
There was the one rumor that Boston would have very much been interested in Chandler Parsons. But who wouldn't be? Parsons is young, athletic, talented and still plays on a rookie, second-round pick contract. That's the kind of real value that is very much at a premium in today's NBA.
Morey's jumping-the-checkers-all-over-the-board approach has been on display for more than a half-decade now. He landed the All-Star pair of James Harden and Dwight Howard with it. So, if he couldn't wallop another another home run this time around, it surely wasn't because he didn't wear out his beloved Blackberry trying. You can't hit the pitches you don't swing at.
Yet for the first time since he began calling the shots in the front office in 2007, the Rockets' general manager didn't feel the same sense of urgency.
"We feel like as a team as we are coming together at the right time," Morey said. "We had a lot of opportunities to mix things up. But we feel like we have a core with stars in Dwight and James and we have a good group around them that we feel good about, and we feel like when you have that core you want to keep the guys around them."
A seemingly endless of string of nagging injuries since the start of the season had prevented the Rockets from developing any cohesion or consistency. Even with Howard back close to his pre-back surgery, pre-shoulder injury level of fitness, there was also the matter of trying to blend his low post game with Harden's one-on-one skills.
While the two of them can sometimes look like would-be dancers with no sense of rhythm, there is a feeling that the pieces are growing together. And the Rockets' record is showing it.
As they close out a five-game road trip with a back-to-back at the Kings and Clippers that starts Tuesday night, the Rockets are now an NBA-best 17-5 since Jan. 1. They have climbed solidly into the No. 3 spot in the Western Conference and now set their sights on the No. 2 Spurs, whom they have already whipped three times this season.
It is a wholly different attitude for Morey, to let the pot he's filled come to a slow boil rather than just keep grabbing for new ingredients. Inside he believes his team still needs that third All-Star level player to stand toe-to-toe with Miami, Indiana and Oklahoma City. But with Howard and Harden contented in their roles on the team, their place in Houston and locked into max-level contracts, patience is probably the most prudent path.
The Rockets were able to trade veteran guard Aaron Brooks, a fan favorite, to Denver because they feel they have enough talent in the pipeline. Last year's draft pick, Isaiah Canaan, plucked in the second round, has been simmering in the NBA D-League and earned his chance to contribute significant minutes with the Rockets. Hamilton is another below-the-radar talent that the Rockets believe can flourish if give the opportunity to play. And it is that cycling through of young players that has kept the Rockets both moving forward steadily in terms of overall progress and flexible enough with their payroll to remain open and available to make that next big deal. As sure as summer follows spring, they'll be standing on the high dive looking to make another big splash in the talent pool in July.
The Rockets would likely be a tough out in any best-of-seven playoff series in the rugged Western Conference, the Thunder included. But with an offense that relies so heavily on the 3-point shot, the question is whether they can perform consistently enough over eight weeks of the playoffs — or even two rounds — to be taken seriously yet.
We'll find out. Sometimes, the answers do come when you sit and wait.
VIDEO: Daryl Morey discusses the Rockets' trade for Jordan Hamilton


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Right now, countries around the world are preparing their proposals for the upcoming World Conference on International Telecommunications (WCIT), which will take place in Dubai this December. During WCIT 2012, the 193 member states of the International Telecommunication Union (ITU), a United Nations agency, will decide whether to impose new regulations on the networks and economics of the Internet.
Specifically, ITU member states will vote on proposed changes to the International Telecommunications Regulations(ITRs), an international treaty last amended in 1988 (long before the commercial Internet existed), that would give the ITU unprecedented regulatory power over the global Internet. As it currently stands, the ITU has no involvement with the Internet whatsoever. Each country gets one vote, and all votes are equal.
Adding to the contentious nature of the process, most of these proposals remain secret, which led to the creation of WCITLeaks.org, where dozens of ITU proposal documents have leaked to the world.
While characterizations of a U.N. "takeover" of the Internet are not precisely accurate — the ITU claims they are outright wrong — the potential consequences remain the same: After WCIT, the governments of the world will have more power over the Internet than ever before — if certain proposed changes to the ITRs are adopted.
In the United States, the federal government and the Internet-related business community stand firmly together in opposition to handing the ITU and its member states any power to regulate the Internet.
To get an insider's take on the process leading up WCIT and what is at stake for Internet users around the world, Digital Trends spoke with former U.S. Ambassador David Gross, a renowned expert on international telecommunications. As a former U.S. Coordinator for International Communications and Information Policy for the Department of State, Amb. Gross has led various U.S. delegations before the ITU. Amb. Gross is now a partner with Weily Rein LLP, and currently represents a range of Internet-related companies, including telecom giants like AT&T and Verizon, as chairman of the Information, Communications, and Technology Policy Committee of the U.S. Council for International Business.
Amb. Gross is in Bangkok, Thailand, this week for a preparatory meeting of the Asia-Pacific Telecommunity (APT), whose task it is to decide upon the region's various ITU proposals that will be officially presented at WCIT 2012. We spoke with Amb. Gross on Wednesday after the day's APT meeting.
DT: How is the meeting going so far?
Amb. Gross: Well the meeting is going on… Interestingly, this was supposed to be the last preparatory meeting for the APT, but because it could not get through for a variety of reasons, we're going to have to meet again for three or four days at the end of September, or beginning of October. So, that's a significant shift. They thought they were going to get everything done, and they should have gotten everything done in this meeting. But they were unable to do that.
What's causing the delay?
I would say that the primary reason for the delay is less substance and more the fact that the Iranian delegate, who we all know very, very well — he's the primary Iranian spokesperson at the ITU — has made earlier today well over 200 interventions. He just constantly intervenes, and constantly makes very lengthy interventions as well. And so that has just sucked up virtually all of the time. Very few of the other delegations here actually make any interventions. The other countries that make some interventions are Australia, Korea, Japan, and occasionally China — but only occasionally. And virtually none of the others. And so it's all because of one nonsense intervention after another by the Iranians.
So it's a stonewalling tactic?
It sounds like that. But in fact, it's even stranger, in my view. It's less that he's trying to do this for some tactical effect, which is what you would expect if you were really trying to stonewall. But rather he just has a personality that requires him to intervene, to correct, and to perfect on non-substantive grounds everything. And he does it in a style that requires it to be a lengthy intervention. So you put those things together, and it doesn't appear to be for tactical or strategic reasons. It's actually psychological reasons.
Let's take a step back. What is your role in the APT meeting, and what is the meeting's basic purpose?
My role here is as an observer. I am here as an observer on behalf of an ad hoc coalition of companies that I chair — currently 15 companies, substantial companies, that are interested in what happens with regard to the Internet, particularly international regulation and the like. There is a U.S. delegation, which is actually representing CITEL, which is the Americas' telecom group. So there are representatives here from the FCC, Department of State, Department of Commerce. There are other country observers as well — Canada, for example, and elsewhere.
But the purpose of this meeting was for the Asia-Pacific Telecommunity, which represents all the Asian countries getting prepared for WCIT, which will be held in Dubai in December. [The meeting is] to help prep common positions for the region. All of the regions of the world have these. What was going to be very important about this one is, it was going to be the first region to come to these agreements in the final stages of the process. So, in theory, it could have and should have been a template for all the other regions going forward for these negotiations. But they missed the opportunity here by failing to finalize their proposals. They won't be final until the end of October, beginning of November. The importance of the meeting, frankly, has gone down significantly.
Will some other region take the lead?
Over the next month or so, there will be meetings like this for the Americas, in El Salvador. There will be meetings for Europe, set in Copenhagen. There will be meetings in the Arab world, in Dubai. There will be meetings for the African communications union in that same period. So there will be meetings for each of the major regions that will look at the same sorts of issues.
I do not believe that any other regions, however, are likely to be able to set the global pace, set the template, the way that Asia could have done if they finished their homework today, just as a practical matter. Now, each region looks at these things independently. And come early October, there will be a meeting in Geneva where all of the regional groups will provide over a day and a half a report on where they are in terms of their process, and report out all of these things. But I think in fact we'll have a lot of chaos between now and Dubai as a result of this.
What changes can we expect to see?
Maybe it would be helpful to outline what I think are the currently the most contentious areas without predicting how they will come out because that's too hard to do at this state.
For example, let me start with a sort of overarching issue, which is: Should the ITRs be revised in such a way as to effect directly or indirectly the Internet? The last time they were done, in 1988, they really focused at a very high level only on international telephony. So there's an overarching question of whether or not they should be revised to make them up-to-date, and in so doing, whether or not it should capture Internet-related issues.
Now, the U.S. position that was articulated last week — and of course, I will quickly add, the position of the coalition that I have the honor of chairing — have very strong and very direct views on that. The answer is: No, that the revision should be limited only to international telephony-related issues. That it should basically just update and revise the 1988 treaty, and should not expand the jurisdiction of the ITU any further. That's clearly one of the hot button issues of the conference.
Second — and related, to a certain degree — and we saw this here in Bangkok over the past couple of days is the issue of security: A number of countries, Russia and China and others, are pressing very, very hard for there to be provisions in the ITRs that go to security. The text coming out of Bangkok for AT&T refers only to network security for telecommunications. And the Chinese are very interested in trying to keep the focus on that type of security here, to try to say that they're not tying to use this as a way to regulate the Internet. However, of course, others disagree, and look at the language, and look at the concept, and think that it in fact it looks like it is potentially regulating the Internet, or at least security-related Internet issues. And that obviously is highly problematic for many countries.
The next set of issues is whether or not there should be changes made that would affect the ability of carriers and content providers and others to freely negotiate without governmental or intergovermental interferrences — the terms associated with interconnection, and in this case, Internet [peering] and the like. So, currently, there's no international rules with regard to those issues, at least in terms of peering and the like. And the European carriers — ETNO is the trade association there — has put in a proposal that they're shopping very heavily that would require ITU and governmental intervention into those agreements, and require that the negotiations follow a certain format and include the possibility of having "sender party pays," which would be a radical change to the economics of the Internet.
Next page: Amb. Gross explains how the Internet could change fundamentally for all users, censorship, and more.


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ILEA Academy in Roswell Notes Seventh Anniversary, Sept. 24, 2008
By Jack Swickard
ROSWELL, N.M., Sept. 24, 2008 — The International Law Enforcement Academy in Roswell, a division of New Mexico Tech, began its seventh year of operation this month as the United States marked the seventh anniversary of the 9/11 terrorist attacks.
The attacks by foreign terrorists on the World Trade Center towers in New York City and the Pentagon in Washington on Sept. 11, 2001, coming just a week after the first pilot class at ILEA-Roswell began meeting, illustrated clearly — and terribly — the importance of international police cooperation to the security of the United States and the entire world.
Fostering such cooperation and building law-enforcement networks among participating countries and the United States is a key purpose of the State Department's ILEA program.
Frank Taylor, general manager of ILEA-Roswell and former New Mexico State Police chief, said he considers the networks established between officers of different countries one of the most important results of ILEA.
"During the time I've been here, this very impressive program has helped in networking among various countries that have attended," he said. The networking has resulted in good sharing of information, "something that has worked quite well between the U.S. and attending countries.
"Getting to know these people has helped immensely in establishing relationships on a personal, as well as a professional level," he added.
The State Department began the ILEA program in 1995 after a speech President Bill Clinton delivered to the United Nations General Assembly on Oct. 22, 1995, during the U.N. 50th anniversary. In the speech, Clinton called for a network of international law enforcement academies throughout the world to combat international drug trafficking, terrorism and other transnational crimes through strengthened international cooperation.
The program now has six sites around the world — four regional academies, at Budapest, Hungary; Bangkok, Thailand; Gaborone, Botswana; and San Salvador, El Salvador; a regional training center for Latin America at Lima, Peru; and the center for advanced training at Roswell.
ILEA-Roswell began classes in the deBremmond National Guard facility at the Roswell Industrial Air Center in September 2001. The Roswell academy offers an advanced management course for mid- and upper-level law-enforcement personnel, focusing on the academic aspects of law enforcement rather than its practical aspects. Classes typically include 35 to 50 participants selected from among graduates of regional ILEAs. To date, the Roswell academy has hosted 2,759 delegates from 85 countries, speaking 27 languages.
The current class, which includes 52 delegates from Cambodia, Indonesia, Laos and Vietnam, is the 71st at ILEA-Roswell.
In January 2005, ground was broken for the ILEA building at RIAC. The building was dedicated Feb. 22, 2006, and provides up-to-date classroom facilities that include sophisticated equipment allowing for simultaneous translations of lectures into multiple languages at once. The State Department's Office of Language Services provides simultaneous interpreters, who translate lectures 2 to 2.5 seconds behind the instructors.
New Mexico Tech operates ILEA-Roswell under a cooperative agreement with the State Department. Tech carries out ILEA operations through a consortium that includes Eastern New Mexico University-Roswell, Sam Houston State University and Science Applications International Corp. (SAIC).
Dr. Van Romero, vice president for research and economic development at New Mexico Tech, oversees the ILEA-Roswell program as project director.
Romero said he believes the ILEA-Roswell program has been beneficial for the nation, as well as for the local community.
"We feel the ILEA program helps strengthen U.S. relationships with developing countries in areas vital to national security," he said. "The more countries that get involved, the better the program."
Dr. Dan Walsh is the New Mexico Tech program director for ILEA-Roswell and Josh Carrillo serves as program manager.
Sam Houston State provides 50 to 60 percent of instructors for ILEA-Roswell, under the coordination of Dr. Dick Ward, who still retains some involvement with Sam Houston State, although he is now dean of criminal justice at the University of Connecticut. The remainder of instructional staff is coordinated through SAIC.
The wisdom of establishing the advanced ILEA course in Roswell has been demonstrated over and over again.
In Roswell, senior law enforcement officials from emerging democracies discover what typical Americans are really like, away from the centers of political and economic power of Washington and major metropolitan areas. Many have remarked on the friendliness and helpfulness of local residents, as well as ILEA staff.
Roswell residents open their homes for get-togethers with ILEA delegates, who interact with local residents daily. It is common to see the delegates around the community after class.
Taylor terms the involvement of the Roswell community "one of the biggest successes of this program."
"Their support has really helped, not only with the program, but in establishing relationships with people," he said. "Their support has been excellent."
In a typical comment, Felix Villanueva Mejia, deputy commissioner of the National Police of Honduras, said the warmth of ILEA staff and local residents "made us feel as if we were in our own homes."
Oscar Hernandez, commissioner of the National Police of Nicaragua, was impressed by "the respect that has been shown to us, the friendship and kindness of the people."
The treatment they receive in Roswell has changed negative perceptions of Americans some delegates held before coming to ILEA. What they find in Roswell is that Americans don't fit the stereotypes fostered by Hollywood and by Cold War propaganda; they are warm, friendly and helpful and in many ways are like the people of their own countries.
In the four weeks they are in Roswell, delegates develop such strong bonds with local residents, as well as with ILEA staff and other delegates, that many leave with tears in their eyes, and many develop friendships that last long after the course is over.
Delegates have expressed their appreciation for their hosts from the very first class. After the 9/11 attacks, members of the first ILEA pilot class donated blood for the victims of the attacks.
On Nov. 4, 2002, Roswell Police Officer Cruz Zavala, who had survived being shot five times by a criminal suspect, was officially given a certificate by the Hungarian delegation recognizing him as an honorary Hungarian police sergeant.
People in Roswell also have provided support and encouragement to delegates in difficult times. After a tsunami devastated the Indian Ocean, including the coast of Thailand, then-Mayor Bill Owen designated the Dec. 30, 2004, as Royal Thai Police Recognition Day as a way of showing the community's support for delegates from Thailand as their country dealt with the tsunami's destruction.
Roswell residents also benefit through expanded horizons as they interact with people from a variety of cultures around the world.
They benefit in other ways, too, sometimes unexpectedly. A young woman who lived in Roswell became lost while vacationing in southern Africa. She had left her passport at the hostel where she was staying.
As she was returning to the hostel on board a bus, she failed to get off at her stop and spent two hours on the bus. The bus driver dropped her off at a police station, where she discovered several officers who had attended ILEA-Roswell. One of the policemen, accompanied by a woman employee, drove the Roswell woman back to the hostel.
ILEA-Roswell delegates have had a wide variety of backgrounds and have included the chief of environmental law enforcement for Brazil, an art theft investigator from Poland, the head of the Colombia National Police Human Rights Office and a member of the Seychelles Supreme Court.


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- Chapter 1
If any of you lack wisdom, let him ask of God—Resist temptation—Be doers of the word—James explains how to recognize pure religion.
- Chapter 2
God has chosen the poor of this world who are rich in faith—Salvation is gained by keeping the whole law—Faith without works is dead.
- Chapter 3
By governing the tongue, we gain perfection—Heavenly wisdom is pure, peaceable, and full of mercy.
- Chapter 4
Wars are born of lusts—The friends of the world are the enemies of God—Sin is failure to walk in the light we have received.
- Chapter 5
Misery awaits the wanton rich—Await the Lord's coming with patience—The elders are to anoint and heal the sick.


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Internet Primary Sources for Teaching Womens Rights
General History Websites
Feminist Foremothers: 1400 to 1800 (some primary source excerpts)
Feminist Forefathers: some excerpts from early pro-women writers
Internet Women's History Sourcebook
Other Womens Voices: Translations of women's writing before 1700
Women and Social movements in the United States, 1600-2000; Women lesson plans. six document-based question units.
World History Connected, Lyn Reese,Her Marriage Bondage: Useful Websites for Linking Womens Marriage Rights Past to Present
Traditional Sayings & Inspiring Quotes
Code of Hammurabi, (c. 1780 BCE)
Code of Assura Assyrians (c.1975 BCE)
Inheritance Law of and through Women in the Middle Assyrian Period: (PDF document)
Ischomachus's Wife: The Economist by Xenophon (c. 430-355 BCE)
Great Code of Gortyn (Crete, c. 450 B.C.E.)
Womens Legal Status in Roman World: Find The Twelve Tables (excerpt): Gaius, on guardianship. Marriage Laws, Julian marriage laws (Emperor Augustus c. 18 BCE)
Justinian Code. (533 CE): selections that follow the first part code.
Ban Zhoa (c 48-120 BCE), China.
The Mother of Mencius, (c. 372 289 BCE), China; short text.
Indian History Sourcebook: Kautilya
Laws of Manu, (c. 500 BCE - 200 CE) India: compendium of ancient sacred laws and customs by the orthodox adherents of Brahminism. Lesson included.
Womens Speeches to the Roman Forum: (195 & 42 B.C.E.)
Greater Learning for Women (Japan, 1762)
Queen Eleanor of Aquitaine: Peter of Blois letter to Chastise Her (1173)
Magdeburg Law: (1261) Germany
Christine de Pizan, (1364-ca.1431) A Medieval Woman's Mirror of Honor, The Treasury of the city of Ladies, France.
Letters of Isotta Nogarola (Italy, cs 1418-1466)
Margaret Fell, Womens Speaking Justified (England, 1666)
Advice Books on mariage: William Gouge, Of Domesticall Duties (1622)
Homily appointed to be read in Churches in time of Queen Elizabeth I
Quotes from Mary Astell, England, (1700)
Mary Wollstonecraft debates Jean-Jacque Rousseau, (1791)
Womens Petition to the National Assembly, France, 1789
Short excerpts from women in Revolutionary France
Olympe De Gouges, Declaration of the Rights of Woman, France, (1791)
French Civil Code: Napoleonic Codes, (1803)
Caroline Norton , England, (1824 &1855)
A Letter to the Queen on Lord Chancellor Cranworth's Marriage and Divorce Bill Caroline Norton, (1855)
Seneca Falls Declaration of Sentiments and Resolutions, U.S.A., (1848)
Ernestine Rose, Womens Rights Convention, U.S.A., (1851)
Womans Rights and Womens Wrongs: Pro and Con Womens Rights, U.S.A., (1867-68)
John Stuart Mill, The Subjection of Women England, (1869)
United States vs Susan B. Anthony: Anthony Statement: (June 17-18, 1873)
Gaining Womens Suffrage in Great Britain (1906-1918)
Maria Eugenia Echenique: The Emancipation of Women, Argentina, (1876)
Meiji Civil Code of 1898 and Kishida Toshiko, Japan, (1863-1901)
Qasim Amin The Liberation of Woman (1899), and Chronology of Major Events of womens rights, Egpyt, (1873 - 1994)
Malik Hefni Nassef (pen name Bahithat al-Badiyya), lecture (1909), Egypt
Raden Ajeng Kartini, Give the Javanese Education, Indonesia, (1899 - 1904)
Selected Writings of Margaret Sanger
Woman and the New Race: Chapter II Womens Struggle for Freedom: Margaret Sanger, (1920)
A Plan for Peace Margaret Sanger, (1924)
Hiratsuka Haru (Raicho) Japan, (1911)
Interview with Alice Paul about Equal Rights Amendment (1923-25)
Alexandra Kollontai: Communism and the Family, Russia, (1920)
Li Kuei-ying Marriage Law of 1950, China, (1960)
Broadside: Why we opposed votes for women, National Association Opposed to Woman Suffrage, New York City, (1894)
Satirical Cartoon, Womens Emancipation: Harpers Bazaar, 1851, and text by Theodosia E. Bang, Boston, explaining that women wearing pants is form of emancipation.
Contemporary Human Rights Organizations and Treaties
Convention on the Elimination of All Forms of Discrimination against Women (CEDAW) and Declaration on the Elimination of Violence against Women: excerpts.
From Global to Local program: alternative reports from non-governmental groups in countries assessing the process toward implementing CEDAW.
Special Rapporteur: 1996 summary of types of violence.
Declaration on the Protection of Women and Children in Emergency and Armed Conflict.
Women Living Under Muslim Laws: an international solidarity network. top site.
Feminist Majority Foundation: global updates.
Equality Now: domestic violence, reproductive rights, trafficking, and political participation.
Association for Womens Rights in Development (AWID)
Womens Human Rights Resources
WWW reaching women: way to find womens organizations aroung the world.
Global List of Womens Organizations
UNIFEM: Note updated news on actions around the world.
Women, ink. See book Gains and Gaps in Worlds Women 2006.
Women Watch: Information and Resources on Gender Equality and Empowerment of Women. Top site.
Human Rights Watch: Womens Property Rights: Violations Doom Equality and Development. case study to introduce issues property rights.
Lyn Reese is the author of all the information on this website
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Women in World History Curriculum


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MILLEDGEVILLE, Ga. – The No. 29 Georgia College men's tennis team (8-7, 2-5 PBC) notched an important Peach Belt Conference (PBC) victory over No. 25 North Georgia, taking down the Saints impressively 8-1 at the Centennial Center Tennis Facility.
Senior student-athletes Jerome Leborgne (Coordimanche, France) and Leo Bernardes (Sao Paulo, Brazil) didn't disappoint in their final home matches, picking up four victories for the Bobcats.
Leborgne paired with Johan Wadstein (Helinsgborg, Sweden) at the top doubles position to take down Mateus Camasmie and Felipe Friedrich by a score of 8-3. Leborgne went on to defeat Friedrich at the first singles spot 6-2, 6-4, as well.
At the third doubles spot Bernardes teamed with Wictor Andersson (Karlskoga, Sweden) to beat Giovani Santos and Brandon Sloan easily 8-1. Bernardes would also win his singles match over Mathew Guida 0-6, 6-0, 6-4 at the third singles spot, giving him his 10th singles victory of the season.
At the second doubles position, Kasper Konyves (Helsingborg, Sweden) and Tyler Franks (Greensboro, Ga.) fell to Guida and Rodrigo Magan 8-5.
That would be the lone Bobcat loss on the day, as Alex Schubert (Frankfurt, Germany) notched a 6-2, 6-1 win over Santos to get the 'Cats back on track.
Wadstein would pick up the match-clinching victory for the Bobcats with a 6-3, 6-2 win against Camasmie, giving him double-digit singles wins on the year.
Andersson would match his classmate with a 6-2, 6-4 win of his own at the final singles spot against Sloan, while Konyves added one of his own for good measure topping Magan 6-3, 7-5 at the fourth slot.
The Georgia College men will head to No. 12 Augusta State University Friday, April 13 for another important PBC matchup.
The Georgia College Department of Athletics, two-time winners of the PBC Commissioner's Cup, sponsors 10 varsity athletic programs at the NCAA Division II level. As a Division II program, Bobcat Athletics prides itself on balancing the life of the student-athlete, evidenced by the teams' multiple appearances in post-season competition as well as documented academic success and community-service involvement. Sign up at www.twitter.com/BobcatSports and www.facebook.com/gcbobcats for up-to-the-minute reports, and visit www.GCBobcats.com for more information, and to nominate your favorite former Bobcats and Colonials to the GC Athletics Hall of Fame.


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DAYTON - The invasive emerald ash borer is spreading across Ohio, ruining trees and costing local governments and taxpayers.
DAYTON � The invasive emerald ash borer is spreading across Ohio, ruining trees and costing local governments and taxpayers.
The exotic Asian beetle has been in Ohio nearly a decade.
�Just as a wildfire often spreads by sparks from the main fire, so the emerald ash borer is spreading through the state,� said Joe Boggs, an Ohio State University Extension Services educator. �Once these little, crackling fires are established, the population starts building until it explodes into full conflagration.�
The toll is mounting, too. Besides causing local governments to divert funds for eradication efforts, the borers are causing homeowners to pay for insecticide treatments and private contractors for tree removal. Communities and neighborhoods are losing tree canopies, and there is also the loss of hardwood.
�Every community, every homeowner, should be thinking about the effect the emerald ash borer is having,� said Wendi Van Buren, state Department of Natural Resources urban forester.
Authorities suspect the borer arrived amid shipments from Asia. It�s blamed for killing tens of millions of trees in Canada and the United States. Its larvae tunnel beneath bark, disrupting the tree�s ability to take food and water, and eventually killing it.
The city of Dayton has spent $40,000 this year to remove 200 diseased ash trees and replace them. In suburban Springboro, city officials say they are spending $10,000 to $15,000 a year to remove and replace ash trees. The number damaged since the borer showed up in the area in 2006 �is beyond count,� said Vince Murphy, Springboro assistant public works director.
The Heatherwood Golf Course in southwestern Ohio recently took down 110 infested trees.
Some localities are developing plans to cope with the ash borer, including using insecticides to preserve their mature, larger ash trees.
Brian Shuler, a certified arborist with Dayton-based Tree Care Inc., said treatments for mature ash trees can cost hundreds of dollars annually. Removal also costs hundreds, and he recommends that trees be removed after infestation and before they are dead.
�When it is living, ash is an incredibly strong wood,� Shuler said. �When it dies, it quickly becomes brittle.�
Boggs and other experts recommend that homeowners consult with extension agents or arborists before making decisions on how to deal with the problem.
In suburban Beavercreek, park superintendent Mike Thonnerieux said the city�s budget doesn�t have enough money to keep up.
�That�s our bigger concern,� he said. �You wonder how this will impact the city as a whole.�