text:
|Publication number
|Publication type
|Application number
|Publication date
|Mar 21, 2006
|Filing date
|Feb 25, 2005
|Priority date
|Dec 8, 2001
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|Publication number
|ZiQing Li, ZhenQiu Zhang, Long Zhu
|Original Assignee
|Microsoft Corp.
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|Non-Patent Citations (2), Referenced by (26), Classifications (15), Legal Events (3)
|External Links: USPTO, USPTO Assignment, Espacenet
This is a continuation of a prior application entitled "A METHOD FOR BOOSTING THE PERFORMANCE OF MACHINE-LEARNING CLASSIFIERS" which was assigned Ser. No. 10/091,109 and was filed Mar. 4, 2002, which claimed the priority of provisional application No. 60/339,545 filed on Dec. 1, 2001.
1. Technical Field
This invention is directed towards a statistical learning procedure that can be applied to many machine-learning applications such as, for example, face detection, image retrieval, speech recognition, text classification, document routing, on-line learning and medical diagnosis. Although the statistical learning procedure of the present invention is described as applied to a face detection system, the process can be used for boosting the performance of classifiers in any type of classification problem.
2. Background Art
Boosting is an approach to machine-learning classification problems that has received much attention of late. Boosting algorithms have recently become popular because they are simple, elegant, powerful and easy to implement. Boosting procedures have been used in many different applications. For instance, Fan, Stolfo and Zhang [2] introduced boosting, namely a boosting algorithm called AdaBoost, into a distributed online learning application. Iyer, Lewis, Schapire, Singer and Singhil [8] applied boosting to document routing, employing a boosting procedure for classifying and ranking documents in the context of Information Retrieval (IR). Moreno, Logan and Raj [13] employed a boosting classification algorithm in the confidence scoring of data in speech recognition application. They derived feature vectors from speech recognition lattices and fed them into a boosting classifier. This classifier combined hundreds of very simple 'weak learners' and derived classification rules that reduced the confidence error rate by up to 34 percent. Schapire and Singer [23] used a family of boosting algorithms to perform text and speech categorization tasks. Sebastiani, Sperduti and Valdambrini [25] also applied boosting to text categorization. Tieu and Viola [30] applied boosting to image retrieval.
In most classification problems, feature vectors are composed and fed into one or more classifiers. There are usually just a few types of features used, such as, for example, color and oriented edges found in a training image. Boosting typically combines hundreds or thousands of very simple classifiers, called 'weak learners', by using a weighted sum. A classification procedure is iteratively applied to a set of weighted feature vectors. Each weak learner is called upon to solve a sequence of learning problems. At first each feature vector is assigned an equal weight (or a weight depending on its prior probability). At each iteration, a classifier is learned and the feature vectors that are classified incorrectly have their weights increased, while those that are correctly classified have their weights decreased. That is, in each subsequent problem examples are reweighted in order to emphasize those which were incorrectly classified by the previous weak classifier. Each classifier focuses its attention on those vectors on which the previous classifier fails. The concept is that feature vectors that are difficult to classify receive more attention on subsequent iterations.
The classifier learned at each iteration is called a "weak classifier". A weak classifier is one that employs a simple learning algorithm (and hence a fewer number of features) and is not expected to classify the training data very well. Weak classifiers have the advantage of allowing for very limited amounts of processing time to classify an input. The final classifier, the "strong classifier", is formed as a weighted sum of the weak classifiers learned at each iteration. One important goal for many machine-learning applications is that the final classifiers depend only on a small number of features. A classifier which depends on a few features will be more efficient to evaluate a very large database, requiring less processing time and resources. Furthermore, the use of boosting classifiers with the choice of weak learners offers the advantage of being less sensitive to spurious features. It has been shown that the training error of a strong classifier approaches zero exponentially in the number of iterations.
It is noted that in the preceding paragraphs, as well as in the remainder of this specification, the description refers to various individual publications identified by a numeric designator contained within a pair of brackets. For example, such a reference may be identified by reciting, "reference [1]" or simply "[1]". A listing of the publications corresponding to each designator can be found at the end of the Detailed Description section.
The present invention is directed toward a procedure that iteratively refines results obtained by a statistically based boosting algorithm to make a strong classifier which is better than can be obtained by the original boosting algorithm in the sense that fewer features are needed and higher accuracy is achieved for many different types of classification problems. The system and method, named FloatBoost, uses a novel method to select an optimum feature set to train weak classifiers based on the selected optimal features, and thereby to construct a strong classifier by linearly combining the learned set of weak classifiers. The boosting algorithm of the present invention leads to a strong classifier of better performance than obtained by many boosting algorithms, such as, for example, AdaBoost, in the sense that fewer features are needed and higher accuracy is achieved. This statistical learning procedure can be applied to many machine-learning applications where boosting algorithms have been employed, such as, for example, face detection, image retrieval, speech recognition, text classification, document routing, on-line learning and medical diagnosis.
In the FloatBoost system and method, simple features are devised on which the classification is performed. Every classifier, or cascade of classifiers, is learned from training examples using FloatBoost. FloatBoost expands upon the AdaBoost procedure. AdaBoost is a sequential forward search procedure using the greedy selection strategy. Its heuristic assumption in the monotonicity, i.e. that when adding a new feature to the current set, the value of the performance criterion does not decrease. A straight sequential selection method like sequential forward search (SFS) or sequential backward search (SBS) adds or deletes one feature at a time. To make this work well, the monotonicity property has to be satisfied by the performance criterion function. However, this is usually not the case for many types of the performance criterion functions such as normally used in AdaBoost. Therefore, AdaBoost suffers from the non-monotonicity problem as a sequential search method.
The Floating Search is a class of feature selection methods that allows an adaptive number of backtracking steps to deal with problems with non-monotonic criteria. While AdaBoost constructs a strong classifier from weak classifiers using purely sequential forward search, FloatBoost allows backtracking search. This results in higher classification accuracy with a reduced number of weak classifiers needed for the strong classifier.
The boosting process of the present invention involves inputting a set of training examples, a prescribed maximum number of weak classifiers, a cost function capable of measuring the overall cost (or overall quality of the strong classifier), and an acceptable maximum cost. A set of candidate weak classifiers is computed, each classifier being associated to a particular feature of the training examples. (A weak classifier is one that employs a single learning algorithm and hence one or a few number of features.) It is then determined which of the set of weak classifiers is the most significant weak classifier given the selected ones. The most significant classifier is based on the feature that when working together with the existing ones is most likely to predict correctly the classification labels of the training examples. This most significant classifier is then added to a current set of optimal weak classifiers. A determination is then made as to which of the current set of optimal weak classifiers is the least significant classifier. The least significant classifier is the one which when removed will lead to improvement of the overall classification performance. The overall cost for the current set of optimal weak classifiers is computed using the cost function. The least significant classifier for the current set of optimal weak classifiers is then conditionally removed and the overall cost for the current set of optimal weak classifiers is then re-computed, less the least significant classifier. It is then determined whether the removal of the least significant classifier results in a lower overall cost. Whenever it is determined that the removal of the least significant classifier results in a lower overall cost, the least significant classifier is eliminated. While keeping the earlier optimal weak classifiers unchanged, each classifier in the current set of optimal weak classifiers associated with a feature added subsequent to the eliminated classifier is then recomputed. The foregoing actions of computing the overall cost for the current set of optimal weak classifiers using the cost function, through recomputing each classifier in the current set of optimal classifiers associated with a feature added subsequent to the eliminated classifier while keeping the earlier optimal weak classifiers unchanged, are repeated until it is determined the removal of the least significant classifier does not result in a lower overall cost. At this point, the last identified least significant classifier is then reinstated to the current set of optimal weak classifiers. Next it is determined if the number of weak classifiers in the current set of optimal weak classifiers equals the prescribed maximum number of weak classifiers or the last computed overall cost for the current set of optimal weak classifiers exceeds the acceptable maximum cost. Whenever it is determined that the number of weak classifiers in the current set of optimal weak classifiers does not equal the prescribed maximum number of weak classifiers and the last computed overall cost for the current set of optimal weak classifiers exceeds the acceptable maximum cost, the foregoing process starting with determining which of the set of weak classifiers is the most significant classifier is repeated. This continues until it is determined that the number of weak classifiers in the current set of optimal weak classifiers does equal the prescribed maximum number of weak classifiers or the last computed overall cost for the current set of optimal weak classifiers becomes lower than the maximum allowable cost, at which point the sum of the individual weak classifiers is output as the trained strong classifier.
The specific features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
In the following description of the preferred embodiments of the present invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. It is understood that other embodiments may be utilized and structural changes may be made without departing from the scope of the present invention.
1.0 Exemplar Operating Environment
The invention is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the invention include, but are not limited to, personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
With reference to
Computer 110 typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 110 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer 110. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of the any of the above should also be included within the scope of computer readable media.
The system memory 130 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM)b 131 and random access memory (RAM) 132. A basic input/output system 133 (BIOS), containing the basic routines that help to transfer information between elements within computer 110, such as during start-up, is typically stored in ROM 131. RAM 132 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 120. By way of example, and not limitation,
The computer 110 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only,
The drives and their associated computer storage media discussed above and illustrated in
The computer 110 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 180. The remote computer 180 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 110, although only a memory storage device 181 has been illustrated in
When used in a LAN networking environment, the computer 110 is connected to the LAN 171 through a network interface or adapter 170. When used in a WAN networking environment, the computer 110 typically includes a modem 172 or other means for establishing communications over the WAN 173, such as the Internet. The modem 172, which may be internal or external, may be connected to the system bus 121 via the user input interface 160, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 110, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation,
The exemplary operating environment having now been discussed, the remaining parts of this description section will be devoted to a description of the program modules embodying the invention.
2.0 The FloatBoost Learning Procedure
The FloatBoost learning procedure is a statistically-based boosting procedure that makes it possible to train accurate classifiers in many different types of classification problems. FloatBoost uses a novel method to select optimum features and to train classifiers. It boosts classification performance by linearly combining a set of weak classifiers to form a strong classifier.
2.1 Overview.
In the most general sense, as shown in
More specifically, the FloatBoost learning procedure is described as follows. Let
(1) Training examples Z={(x1; y1), . . . ,(xN; yN)}, where N=a+b; of which a examples have yi=+1 and b examples have yi=−1;
(2) The maximum number Mmax of weak classifiers to be combined;
(3) The cost function J(HM) (e.g., error rate made by HM);
(4) The acceptable cost J*
1. (Initialization)
for those examples with yi=++1 or
for those examples with yi=−1;
(2) Jm min=max-value (for m=1, . . . ,Mmax)M=0, H0={ };
2. (Forward Inclusion)
(2) Choose hM according to Eq.8;
(3) Update wi (M)←wi (M) exp[−yihM(xi)], and normalize to Σ wi (M)=1;
3. (Conditional Exclusion)
(1) h′=arg minh∈H
(3) else
As mentioned previously, boosting algorithms can be applied to many machine learning applications. The boosting procedure of the invention will be described in terms of face detection. As such, some background information on boosting procedures and face detection systems is useful.
2.2.1 Background Information on Face Detection
Face detection systems essentially operate by scanning an image for regions having attributes that would indicate that a region contains a person's face. These systems operate by comparing some type of training images depicting people's faces (or representations thereof) to an image or representation of a person's face extracted from an input image. Furthermore, face detection has remained a challenging problem especially for non-frontal view faces. This challenge is firstly due to the large amount of variation and complexity brought about by the changes in facial appearance, lighting and expression [1,26]. Changes in facial view (head pose) further complicate the situation because the distribution of non-frontal faces in the image space is much more dispersed and more complicated than that of frontal faces. Learning based methods have so far been the most effective ones for face detection. Most face detection systems learn to classify between face and non-face by template matching. They treat face detection as an intrinsically two-dimensional (2-D) problem, taking advantage of the fact that faces are highly correlated. It is assumed that some low-dimensional features that may be derived from a set of prototype or training face images can describe human faces. From a pattern recognition viewpoint, two issues are essential in face detection: (i) feature selection, and (ii) classifier design in view of the selected features.
A procedure developed by Freund and Shapire [4], referred to as AdaBoost, has been an effective learning method for many pattern classification problems, to include face detection. AdaBoost is a sequential forward search procedure using the greedy selection strategy. Its heuristic assumption is monotonicity, i.e. that when adding a new feature to the current set, the value of the performance criterion does not decrease. The premise offered by this sequential procedure can be broken-down when the assumption is violated, i.e. when the performance criterion function is non-monotonic. As a sequential search algorithm, AdaBoost can suffer from local optima when the evaluation criterion is non-monotonic.
Another issue is real-time multi-view face detection. Previous face detections systems, especially any that can detect faces in multiple viewpoints, are very slow, too slow to be used for real time applications. Most existing works in face detection, including Viola et al. [31] deal with frontal faces. Sung and Poggio [29] partition the frontal face and non-face image spaces each into several probability clusters, derive feature vectors in these subspaces, and then train neural networks to classify between face and nonface. Rowley et al [20] trained retinally connected neural networks using preprocessed image pixel values directly. Osuna el al [15] apply the support vector machines algorithm to train a neural network to classify face and non-face patterns. Roth et al. [19] use a learning architecture specifically tailored for learning in the presence of a very large number of features for the face and non-face classification.
In Viola et al. [31], simple Haar-like features, used earlier in Papageorgiou [16] for pedestrian detection, are extracted; face/non-face classification is done by using a cascade of successively more complex classifiers which are trained by using the (discrete) AdaBoost learning algorithm. This resulted in the first real-time frontal face detection system which runs at about 14 frame per second for a 320�240 image [31]. However, the ability to deal with non-frontal faces is important for many real applications because, for example, statistics show that approximately 75% of the faces in home photos are non-frontal [11]. A reasonable treatment for multi-view face detection is the view-based method taught by Pentland et al. [17], in which several face models are built, each describing faces in a certain view. This way, explicit 3D modeling is avoided. Feraud et al. [3] adopt the view-based representation for face detection, and use an array of five detectors with each detector responsible for one view. Wiskott et al. [32] build elastic bunch graph templates for multi-view face detection and recognition. Gong and colleagues [6] study the trajectories of faces in linear Principal Component Analysis (PCA) feature spaces as they rotate, and use kernel support vector machines (SVMs) for multi-pose face detection and pose estimation [14,12]. Huang et al. [7] use SVM's to estimate facial poses.
The system of Schneiderman and Kanade [24] is claimed to be the first algorithm in the world for multi-view face detection. Their algorithm consists of an array of five face detectors in the view-based framework. Each is constructed using statistics of products of histograms computed from examples of the respective view. However, it is very slow and takes one minute to work on a 320�240 pixel image over only four octaves of candidate size [24].
2.2.2 FloatBoost Applied to Detector-Pyramid Face Detection System and Method
The application of FloatBoost to face detection will now be described as it applies to a detector-pyramid architecture designed to efficiently detect multi-view faces. This detector-pyramid system and method is the subject of a co-pending application entitled "A SYSTEM AND METHOD FOR MULTI-VIEW FACE DETECTION", which has the same inventors as this application and which is assigned to a common assignee. The co-pending application was filed on Mar. 4, 2002 and assigned Ser. No. 10,091,100.
In the system and method of the co-pending application, a coarse to fine strategy is used in that a sub-window is processed from the top to bottom of a detector pyramid by a sequence of increasingly more complex face/non-face classifiers designed for increasingly finer ranges of facial view. This strategy goes beyond the straightforward view-based method in that a vast number of nonface sub-windows can be discarded very quickly with very little loss of face sub-windows. This is very important for fast face detection because only a tiny proportion of sub-windows are of faces. Since a large number of nonface sub windows are discarded the processing time for face detection is significantly reduced. The multi-view face detection system employing FloatBoost is distinguished from previous face detection systems in its ability to detect multi-view faces in real-time. It is designed based on the following thinking: While it is extremely difficult to distinguish multi-view faces from non-face images clearly using a single classifier, it is less difficult to classify between frontal faces and non-faces as well as between multi-view faces and parts of non-faces. Therefore, narrowing down the range of view makes face detection easier and more accurate for that view.
More specifically, the detector-pyramid architecture, generally shown in
The multi-view face detection system employing FloatBoost can be generalized as follows. Images of face and non-face examples are captured to be used as a training set. A pyramid of detectors, increasing in sophistication and complexity and partitioned into finer and finer pose ranges from top down, are trained. Then, an input image is prepared for input into the detector pyramid by extracting sub-windows from the input image into sub-windows. Each of these sub-windows is then input into the detector pyramid. For each input sub-window the system determines whether the sub-window is a face, and if so, its pose range. If more than one detector of the present invention detects a face at close to the same location then the system arbitrates the outputs for the detectors with overlapping detections. The following paragraphs detail the generalized process actions discussed above.
As with most face detection system, the face detection system and process employing the detector pyramid must first be trained before it can detect face regions in an input image. This training phase generally involves first capturing face and non-face images. As will be explained later, these captured face and non-face images are used to train a detector-pyramid that employs a sequence of increasingly more complex face/non-face classifiers designed for detecting increasingly finer ranges of facial views. Each classifier is dedicated to detecting a particular pose range. Accordingly, the captured training face images should depict people having a variety of face poses.
The captured training face images are preprocessed to prepare them for input into the detector pyramid. In general, this involves normalizing and cropping the training images. Additionally, the training images are roughly aligned by using the eyes and mouth. Normalizing the training images preferably entails normalizing the scale of the images by resizing the images. It is noted that this action could be skipped if the images are captured at the desired scale thus eliminating the need for resizing. The desired scale for the face is approximately the size of the smallest face region expected to be found in the input images being searched. In a tested embodiment, an image size of about 20 by 20 pixels was used with success. These normalization actions are performed so that each of the training images generally match as to orientation and size. The face training images (but not the non-face training images) are also preferably cropped to eliminate unneeded portions of the image that could contribute to noise in the training process. It is noted that the training images could be cropped first and then normalized.
The high speed and detection rate depend not only on the detector-pyramid architecture, but also on the individual detectors. Three types of simple features, which are block differences similar to steerable filters, are computed as shown in
A face/nonface classifier is constructed based on a number of weak classifiers where a weak classifier performs face/non-face classification using a different single feature, e.g. by thresholding the scalar value of the feature according the face/non-face histograms of the feature. A detector can be one or a cascade of face/nonface classifiers, as in [3]. A more technically detailed description of feature selection and detector training using the FloatBoost procedure will be discussed shortly.
The detectors in the pyramid are trained separately, using different training sets. An individual detector is responsible for one view range, with possible partial overlapping with its neighboring detectors. Due to the symmetry of faces, it is necessary to train side view detectors for one-side only, and mirror the trained models for the other side. For one feature used in left-side view, its structure is mirrored to construct a new feature used for right-side view. Each left-side view feature is mirrored this way, and these new features are combined to construct right side view detectors. Making use of the symmetry of faces, it is necessary to train, for each level, the frontal view detector plus those of non-frontal views on one side. Therefore, assuming there are L (an odd number) detectors at a level, it is necessary to train only (L+1)/2 detectors. The corresponding models for the other side can be obtained by mirroring the features selected for this side. So, 7 detectors are trained for a detector-pyramid composed of 11 detectors.
The multi-view face detection system and method classifies images based on the value of simple features. The FloatBoost system and method uses a combination of weak classifiers derived from tens of thousands of features to construct a powerful detector. To summarize the above, the construction of the detector-pyramid is done in the following way:
Therefore, using FloatBoost, the detectors in the pyramid are trained separately using separate training sets. An individual detector is responsible for one view/pose range, with possible partial overlapping with its neighboring detectors.
Once the system is trained it is ready to accept prepared input image regions and to indicate if the region depicts a face, even if the face is non-frontal in the image.
2.2.3 Detailed Description of FloatBoost Procedure
This section provides a mathematical description of the FloatBoost boosting procedure as it applies to a face detection application. It should be noted that although this boosting method is described here with respect to its applicability to face detection, the FloatBoost procedure has applicability to many other applications including speech recognition, text classification, document routing, online learning and medical diagnosis.
The multi-view face detection task is the following: Given the input image I, find the locations of all faces in I and give the scale and pose of each found face. Denote the existence of a face by the state S=(u, v, s, θ) where (u, v) is relative translation in the image plane, s the size (scale) of the rectangular sub-window containing a face, and θ is the pose.
Multi-view face detection can be done in three steps: First, scan I exhaustively at all possible locations and scales, resulting in a large number of sub-windows x=x(u, v, s | I). Second, for each x, test if it is a face at pose θ.
Third, post-process to merge multiple detections.
In this section, a statistical framework for learning such a classification function h(x) is presented For the time being, face-nonface classification only is considered and the pose θ is dropped out.
184.108.40.206 Learning Classification Function
For the two class problems, a set of N labeled training examples (x1; y1), . . . (xN; yN) is given, where yi∈{+1,−1} is the class label associated with example xi. For face detection, xi is an image sub-window of a fixed size (e.g. 20�20) containing an instance of the face (yi=+1) or nonface (yi=−1) pattern. In the notion of Real AdaBoost [22,5 ], a stronger classifier is a linear combination of weak classifiers
where hm(x)∈
In boosting learning [4], each example xi is associated with a weight wi, and the weights are updated dynamically using a multiplicative rule according to the errors in previous learning so that more emphasis is placed on those examples which are erroneously classified by the weak classifiers learned previously. This way, the new weak classifiers will pay more attention to those examples. The stronger classifier is obtained as a proper linear combination of the weak classifiers.
188.8.131.52 Learning Weak Classifiers
Here, the following discussion deals with how to derive a (usually large) set of candidate weak classifiers given the (normalized) weights w, and then choose hm(x) from the set. The "margin" of example (x, y) achieved by h(x) (a single or a combination of weak classifiers) on the training examples can be defined as yh(x) [21]. This can be considered as a measure of the confidence of the h's prediction. The following criterion measures the bound on classification error [22]
where Ew( ) stands for the mathematical expectation with respect to w over the examples (xi; yi).
The weak classifiers hm(x) in Eq.(2) are derived stage-wise as the minimizers of J(h). Given the current estimate h(x), an improved estimate h(x)+h*(x) is sought by minimizing J(h(x)+h*(x)) with respect to h*(x). It is shown in [5] that the minimizer is
This result provides a basis for the subsequent constructions of hj*(x). However, the estimates of P(x|y=+1, w) and P(x|y=−1, w) are not available. Therefore, another approach is chosen for the derivation of h*(x).
A large number of simple features are defined for the sub-window x of a fixed shape and size (cf. [33] and the next section), and each simple feature, denoted as xk, takes on a real scalar value. In the following, a candidate weak classifier hj(x) is derived for each single different feature j.
The probability densities of feature j for a sample sub-window x is denoted by Pj(x|y=+1) for the face pattern and Pj(x|y=−1) for the non-face pattern. The two densities can be estimated using the histograms resulting from weighted voting of the training examples. The candidate weak classifiers are designed as
The half log likelihood ratio Lj(x) is learned from the training examples of the two classes, and the threshold T can be adjusted to control the balance between the detection and false alarm rates in the case when the prior probabilities are not known.
The set of the derived weak classifiers, given the weights w, is denoted by
FloatBoost incorporates the idea of Floating Search [18] into AdaBoost [4,22,5] to overcome the non-monotocity problems associated with AdaBoost. Floating Search [18] is a sequential feature selection procedure with backtracking, aimed to deal with non-monotonic criterion functions for feature selection. Feature selection with a non-monotonic criterion may be dealt with by using a more sophisticated technique, called plus-l-minus-r, which adds or deletes l features and then backtracks r steps [28,10]. The Sequential Floating Search method [18] allows the number of back-tracking steps to be (controlled instead of being fixed beforehand. Specifically, it adds or deletes l=1 feature and then backtracks r steps where r depends on the current situation. It is such a flexibility that amends limitations due to the non-monotonicity problem. Improvement on the quality of selected features is gained with the cost of increased computation due to the extended search. The SFFS algorithm performs very well in several applications [18,9]. The idea of Floating Search is further developed in [27] by allowing more flexibility for the determination of l.
These feature selection methods, however, do not address the problem of (sub-) optimal classifier design based on the selected features. FloatBoost combines them into AdaBoost for both effective feature selection and classifier design.
Again, applying the FloatBoost learning procedure to the face detection problem discussed above the actions of training inputs, initialization, forward inclusion, conditional exclusion and output are performed to construct the strong classifier H(x)=sign
For face detection, the acceptable cost J* is the maximum allowable risk, which can be defined as a weighted sum of missing rate and false alarm rate. The algorithm terminates when the cost is below J* or the maximum number M of weak classifiers is reached.
FloatBoost usually needs fewer weak classifiers than AdaBoost to achieve a given objective J*. One has two options with such a result: (1) Use the FloatBoost-trained strong classifier with its fewer weak classifiers to achieve similar performance as can be done by a AdaBoost-trained classifier with more weak classifiers. (2) Continue FloatBoost learning to add more weak classifiers even if the performance on the training data does not increase. The reason for (2) is that even if the performance does not improve on the training data, adding more weak classifiers may lead to improvements on test data [24].
|P. Pudil et al., Floating Search Methods for Feature Selection With Nonmonotonic Criteria Functions, Department of Electronic and Electrical Engineering, University of Surrey Guildford, UK, 1994.
|Robert E. Schapire et al, Improved Boosting Algorithms Using Confidence-Rated Predictions, 1998, Machine Learning, In Proceedings of the Eleventh Annual Conference on Computational Learning Theory, p 80-91.
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|Jun 18, 2010
|Dec 9, 2014
|The Trustees Of Columbia University In The City Of New York
|Systems, methods, and media for performing classification using a boosted classifier
|Oct 26, 2011
|Mar 31, 2015
|Fotonation Limited
|Face or other object detection including template matching
|Dec 2, 2010
|Jun 9, 2015
|Fotonation Limited
|Real-time video frame pre-processing hardware
|Dec 16, 2002
|Aug 28, 2003
|Renato Campanini
|Method, and corresponding apparatus, for automatic detection of regions of interest in digital images of biological tissue
|Sep 30, 2004
|Mar 30, 2006
|Wu Chou
|Method and apparatus for text classification using minimum classification error to train generalized linear classifier
|Apr 29, 2005
|Nov 2, 2006
|Tyng-Luh Liu
|Object-detection method multi-class Bhattacharyya Boost algorithm used therein
|Mar 13, 2007
|Sep 20, 2007
|Kohtaro Sabe
|Information processing apparatus and method, recording medium and program
|Aug 21, 2007
|Feb 21, 2008
|Johnson Kristin D
|Vessel sealing instrument with electrical cutting mechanism
|Oct 3, 2007
|Apr 10, 2008
|Siemens Corporate Research, Inc.
|Method and System For Regression-Based Object Detection in Medical Images
|Sep 27, 2006
|May 29, 2008
|Branislav Kisacanin
|Real-time method of determining eye closure state using off-line adaboost-over-genetic programming
|Mar 21, 2008
|Sep 25, 2008
|Ricoh Company, Ltd.
|Object image detection method and object image detection device
|Mar 20, 2008
|Oct 16, 2008
|Ricoh Company, Ltd.
|Object image detection method and object image detection device
|Nov 21, 2008
|May 27, 2010
|Nvidia Corporation
|Application of classifiers to sub-sampled integral images for detecting faces in images
|Dec 17, 2008
|Jun 17, 2010
|Microsoft Corporation
|Boosting algorithm for ranking model adaptation
|Jun 18, 2010
|Apr 21, 2011
|Pelossof Raphael A
|Systems, Methods, and Media for Performing Classification
|Oct 26, 2011
|May 3, 2012
|DigitalOptics Corporation Europe Limited
|Face or Other Object Detection Including Template Matching
|Mar 30, 2015
|Jul 23, 2015
|Fotonation Limited
|Face or other object detection including template matching
|U.S. Classification
|706/12, 706/47, 706/25, 706/48
|International Classification
|Cooperative Classification
|European Classification
|Aug 19, 2009
|Fee payment
Year of fee payment: 4
|Aug 26, 2013
|Fee payment
Year of fee payment: 8
|Dec 9, 2014
Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MICROSOFT CORPORATION;REEL/FRAME:034543/0001
Effective date: 20141014


text:
Grassland Birds!
Check out our new interactive bird map to learn more about some important bird species we found during our surveys.
View the Map
Virginia Working Landscapes (VWL) is a program of the Smithsonian Conservation Biology Institute (SCBI) that promotes the conservation of native biodiversity and sustainable land-use through research, education and community engagement.

subset: commoncrawl


text:
U29 Steel Support Shandong China Coal - Chinaprice: contact company for price
chinacoal01 U29 steel support , steel support
U29 beam
1. beam is high quality
2. national standard
3. lowest price
Our company mainly manufactures all kinds of mining
products, such as mining support bracket, u beam, mining steel
arches, U 15, U 29, U36, and the assemble accessories.
It is mainly used for mining tunnel support, with the
features of high pressure, long lift, strong structure.
Company Contact:
- Posted By: Shandong China Coal Group
- Phone: 865372350961
- Address: No.11 Kaiyuan Road, Jining, China
- Email:
- Website: http://www.chinacoalintl.com
Published date: April 20, 2015 -
- Business Description: Shandong China Coal Industrial&Mining Supplies Group Co.,Ltd
(hereinafter referred to as china coal) is a group company .which is a
collection of e commerce, machinery manufacturing, software, research
and development, modern logistics of large diversified industrial group.
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text:
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Celeb Snaps! Hottest Star Sightings – Tuesday 03.05.13
Barbara DeFranco
| March 5, 2013 - 1:36 pm
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text:
Marla Foster had learned what every career woman learns in a mans world and so she knew better than to get involved with a client. But how could she ignore the sexy, irreverant sporting goods king whod just given her his multimillion dollar account and an invitation into his strong arms?
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text:
Breakthrough! Bible for Young Catholics
- All Products
- Academic
- Accompaniment Tracks
- Audiobooks
- Bible Accessories
- Bible Covers
- Bible Studies & Curriculum
- Bibles
- Books
- Buy in Bulk
- Catholic
- Children
- Christian Living
- Christmas
- Church & Pastoral
- Church Supplies
- Closeouts
- Clothing & Accessories
- Crafts & Recreation
- Download
- DVDs
- eBooks
- eBooks On Sale
- Family
- Fiction
- Gift & Home
- Homeschool
- Last Chance Bargains
- Music
- New Cyber Deals
- New Release
- Non-Fiction
- Pre-Order
- Slightly Imperfect
- Software
- Spanish
- Streaming Video
- Subscriptions
- Sunday School
- Teens
- Toys
Product Description
Breakthrough! The Bible for Young Catholics hardcover edition, highlights what happens throughout salvation history between God and humanity. God breaks through and connects with human history, thereby establishing a relationship with humanity.
Using the Good News Translation, Breakthrough! The Bible for Young Catholics was created for young people leaving childhood and entering adolescence. Its 10 special features were created to help make the Bible easier for young people to read and understand.
They will learn about the great people of the Bible, and will see how God has been breaking through in human history and connecting with humanity for thousands of years. Most important, they will discover, in the Bible, how God's messages to key people of faith have meaning for life today.
- Excellent text book for classroom or homeschool.
- Children will know and understand God's saving plan revealed through 125 featured story spreads highlighting key Bible passages.
- Vibrant illustrations and borders immediately engage children and allow them to dive in to Scripture and become immersed in the stories.
- Understand It! sections enable children to comprehend central themes by using child-friendly backgrounds and commentary
- Live It! instructions encourage children to apply the meaning of each story to their lives through engaging activities and prayers
- Tell It! frames help children retain and comprehend the passage by having them retell the story in their own words
- Unique navigational features designed specifically for early readers help children easily locate passages and stories
- Intentional design elements such as fonts built for early readers, increased line spacing, bold vocabulary words, colorized text, minimal hyphenation, and simple column dividers help make this a Bible children can read on their own.
- Inserts that focus on Catholic Prayers and Catholic Teachings
- Index of Bible Stories, Events, Prayers, Miracles, Parables, and Jesus' Teaching
- Index of Articles
- Glossary
- Bible Passages for Special Occasions
- Maps
- 8-point text size
- 9.25" x 6.25" x 1.75"
Product Information
|Format: Hardcover
Vendor: Saint Mary's Press
Publication Date: 2013
Dimensions: 9.2 X 6.2 (inches)
Text Color: Black Letter
|Text Size: 8 Point
Thumb Index: No
Ribbon Marker: No
Spine: Glued
Page Gilding: None
Page Edges: White
Related Products
First Communion Bible, GNT New Testament, White Leather-lookLivingstone CorporationZondervan / 2004 / Imitation Leather$9.99 Retail:5 Stars Out Of 5 2 Reviews
$12.99Save 23% ($3.00)
First Communion Bible, GNT New Testament, Black Leather-look - Slightly ImperfectZondervan / 2004 / Imitation Leather$5.99 Retail:
$12.99Save 54% ($7.00)
Breakthrough! The Bible for Young CatholicsSaint Mary's Press / 2013 / Trade Paperback$22.99 Retail:
$26.95Save 15% ($3.96)
First Communion Bible, GNT New Testament, White Leather-look - Slightly ImperfectZondervan / 2004 / Imitation Leather$7.99 Retail:
$12.99Save 38% ($5.00)


text:
2009's are being re-released full force by Nike in 2012. Compared to the '09's, the 12's are shit.
New Videos
Subscribe to the Sneaker News Youtube Channel
September 7, 2011 BY Aaron Hope / 18
The Air Max flagship series from Nike Running featured Flywire uppers during 2009 and '10 and switched to Hyperfuse this year, and it looks like lightweight and super-breathable beats 'just' lightweight, as the Nike Air Max+ 2012 will again feature a two-layered Fuse upper. The silhouette's rounded lines will remind some of the Free Run 2, but you get considerably more cushioning thanks to a heel-to-toe Max Air cushion. If the universe ends next year along with the Mayan calendar, does the Air Max 2012 represent going out on top, or was one of its predecessors more impressive in your eyes? Click through to see four colorways slated for Q2 '12 and stick with Sneaker News for the Nike Air Max 2012 release date. via CK
Filed under: Nike Air Max Running Upcoming Sneakers
Tags: Nike Air Max+ 2012
2009's are being re-released full force by Nike in 2012. Compared to the '09's, the 12's are shit.
I'm a big AM fan, and I've been picking up at least 2 pairs every year, but I might pass on these. I'd kill for a re-release of the 2009's, though. These are trash compared to those.
The pattern on the side is a bit too overdesigned for my taste, simplify it a bit and you've got an alright shoe there. Let's face it though, Nike shoe design peaked from about 87 - 91. AM1, AM90, AM180 and Huarache LE's will never be bettered. The technology might improve but everything Nike makes now is a bit ugly and soulless.
These are dope, they're completely different save the mid & out soles. Young heads always showin there age...
You people are all morons
boring as heck .. they look like the new free runs with an airmax sole .. where is the creativity nike cmon the air max is one of the most important annual models and this is all u got sheesh
why the same sole??
why is the first one different...
looks like an air max 2010.5
omg change the sole
no idea
omg shut up those are pimp
it's an air max. that's the air max sole. what do you suggest they use?
damn, you dont have to agree with me, but you don't have to be an asshole about it.. my comment is +3, while yours has one. who needs to open their eyes now?
Subscribe to the Sneaker News Youtube Channel


text:
The Philadelphia Art Museum (see Sylvester Stallone in Rocky) is an outstanding museum set in a beautiful building right on the Schuylkill River. The permanent collection is varied, with art from all over the world and in different mediums. It's definitely worth a half-day at least.
Adults are $10, Seniors (62+), Students (with I.D.) and kids (13+) are $7, and kids 12 and under are free.
Hours: Tuesday through Sunday 10a- 5p; Wednesday and Friday evenings until 8:45p.; Closed Mondays.
With a splendid location this immense building easily reached by the hop-on hop-off bus, provides great views.
Without time to enter and admire its collection, one of the greatest in USA, we could only appreciate the site, but it deserves the trip, especially if you have time to enter, of course.
Special Exhibits Information: Require advance purchase. You will need to buy tickets in advance and you can do it online. Make sure you choose a time convenient for you, and allow at least an hour to go through the exhibit.
A group of us visited this museum, from "Rocky" fame, on a whim (it was raining and so we opted for this over the zoo). At any rate, while we didn't have the time to do this museum justice, this is definitely one of the nicer art museums I've seen, housing Picasso and all of your other greats, as well as some interesting modern art that will give you an opportunity for interpretation.
Upon first sighting the museum, you may be surprised at its facade, as I was. The coloring is a warm yellow and when you inspect it more cloely you will find Egyptian style columns and motifs. This is not a great picture, as it was a cloudy winter day~check out the website for a better image, and current information!
Established in 1876, the museum opened in 1877. Construction of the current building began in 1919 when Mayor Thomas B. Smith laid the cornerstone in a Masonic ceremony on the former reservoir land of the decommissioned Fairmount Water Works covering ten acres of ground. The Phil. Art Museum describes itself as "one of the largest museums in the United States", and its collections include more than 227,000 objects.
We enjoyed the Strand Photography, Degas exhibit, the cafeteria and coffee shop offered healthy reasonable choices. The gift shops were very impressive.
Hours are 10 to 5 Tuesday to Sunday with late nights Wednesday and Fridays until 8:45. Adult admission is $20 but Wednesday's after 5:00 and the first Sunday of every month are pay what you wish. We have found groupon specials for the museum.
The Art Museum is worth the price of admission just for its world-class art. On Friday evenings, however, there's a bonus for visitors -- live jazz and pop concerts at no additional charge! After several hours of roaming the galleries, relax a little in the Great Hall, either with drinks, dinner (these ARE extra cost), or just sitting down on the stairs. Want a break from the music? Go back into the galleries -- about half (but not all) are still open after 5 pm.
Spend the morning in Old City, the mid-day at Reading Terminal Market, the late afternoon at the Art Museum, and your early evening listening to an intimate concert. It's hard to beat!
Note: smoking is prohibited throughout the Museum, even during jazz concerts.
While glancing a the photos, some may wonder why nobody is sitting against the stones around the steps -- due to safety concerns, that too is prohibited.
The Philadelphia Museum of Art provided my sister and I a day steeped in beauty - we never got to the armor and weapons, but spent the entire day gazing at some of the most beautiful art ever created. One of the best features of the museum is the re-created rooms, from French hotels to Pennsylvania Dutch kitchens. Also, the cafe is fabulous - the day we were there there were African specialties, a cold salad bar, another lovely vegetable bar - everything was very fresh and far from the usual fare. A little pricey, but well worth it. There is also a lovely restaurant. Two gift shops have everything from books to jewelry, including many hand-crafted items. We got there early and parked just outside the back entrance - for free all day!
The Museum of Art, while not quite at the top eschelon of American art musuems, is surely just below it. It is the primary showcase for art in Philadelphia, and one can spend hours to days exploring its many collections. Almost just as popular with tourists are the steps in front of the museum, made famous in the movie 'Rocky'.
During my visit - I made the point of visiting the Museum of Art. Friday night is late night opening at the main building.
There was a concert and I enjoyed a light supper when listening to live jazz.
There is a combined ticket and a shuttle bus to nearby annexes.
The Musts:
1) See Van Gough's Original Sunflowers on display
Who? Anyone who appricates Van Gough or art
Why? Unlike other famous pieces of original work Sunflowers is not croweded with tourists and you will be able to actually photograph yourself next to it
2)Do the Rocky (Run up the steps and get your picture cheering next to his statue)
Who? For any moviefan or just Rocky fan
Why? To say you did it
How? Take SEPTA bus on route 7,32,38,43, or 48
Cost? $16- Adults $12- 13-18 Free- Kids $14- 65+ (first Sunday of the month pay any price)
When? Tues.-Sun. from 10:00 a.m.–5:00 p.m.
Who can forget these famous steps from Rocky? Probably my favourite moment in Philly was running up these steps to the Museum of art to get my compulsory pose photo! Plus geat views of Ben Franklin Parkway and the Philadelphia skyline.


text:
Caliber Collision vs Les Schwab Tire Centers
Start a new comparison
Caliber CollisionService Centers and Repairs
Customers like
No items
Customers don't like
- Never again3
- Turn around time1
Products by Caliber Collision
No items
Les Schwab Tire CentersService Centers and Repairs
Has verified representatives
Customers like
- Location 6
- Polite employees 5
- Availabiity 3
- There are women working there 2
- Toyo tire 2
Customers don't like
- Unwillingness to make things right8
- Do not look at facts of claim5
- Poor customer service5
- Poor management5
- Lousy way i was treated4
Products by Les Schwab Tire Centers
No items
A company's rating is calculated using a mathematical algorithm that evaluates the information in its profile. The algorithm parameters are: users' rating, number of resolved issues, number of company's responses etc. The algorithm is subject to change in future.
Be first to start a discussion.
See also:
Companies are selected automatically by the algorithm.


text:
In today's session Home Depot Inc (HD) registered an unusually high (2,501) contracts volume of call trades. Someone, most probably a professional was a very active buyer of the October, 2016 call, expecting serious HD increase. With 2,501 contracts traded and 54064 open interest for the Oct, 16 contract, it seems this is a quite bullish bet. The option with symbol: HD161021C00134000 closed last at: $0.14 or 30% down. About 501,605 shares traded hands. Home Depot Inc (NYSE:HD) has risen 2.08% since March 2, 2016 and is uptrending. It has underperformed by 6.18% the S&P500.
Analysts await Home Depot Inc (NYSE:HD) to report earnings on November, 15. They expect $1.58 EPS, up 17.04% or $0.23 from last year's $1.35 per share. HD's profit will be $1.95B for 20.35 P/E if the $1.58 EPS becomes a reality. After $1.97 actual EPS reported by Home Depot Inc for the previous quarter, Wall Street now forecasts -19.80% negative EPS growth.
Home Depot Inc (NYSE:HD) Ratings Coverage
Out of 19 analysts covering The Home Depot Inc. (NYSE:HD), 14 rate it a "Buy", 0 "Sell", while 5 "Hold". This means 74% are positive. $156 is the highest target while $106 is the lowest. The $140.98 average target is 9.58% above today's ($128.65) stock price. The Home Depot Inc. has been the topic of 41 analyst reports since August 19, 2015 according to StockzIntelligence Inc. The rating was upgraded by Nomura to "Buy" on Thursday, June 23. The stock of Home Depot Inc (NYSE:HD) has "Buy" rating given on Wednesday, November 18 by UBS. Cantor Fitzgerald maintained it with "Hold" rating and $125 target price in Wednesday, November 18 report. The firm has "Sell" rating by Zacks given on Monday, August 17. The stock has "Outperform" rating given by RBC Capital Markets on Wednesday, November 18. The stock of Home Depot Inc (NYSE:HD) earned "Neutral" rating by Goldman Sachs on Wednesday, April 6. On Wednesday, August 19 the stock rating was maintained by S&P Research with "Hold". The rating was downgraded by Vetr on Wednesday, August 19 to "Buy". The company was downgraded on Saturday, August 29 by Vetr. Topeka Capital Markets initiated the shares of HD in a report on Tuesday, May 24 with "Buy" rating.
According to Zacks Investment Research, "Home Depot is the one of world's largest home improvement retailer. The company offers a level of service unprecedented among warehouse-style retailers. Home Depot stores cater to do-it-yourselfers, as well as home improvement, construction and building maintenance professionals. The Home Depot currently operates in the USA, Canada, Chile, Puerto Rico, and Argentina. The company also operates EXPO Design Centers across the U.S. and Villager's Hardware in New Jersey."
Insitutional Activity: The institutional sentiment increased to 0.92 in 2016 Q2. Its up 0.05, from 0.87 in 2016Q1. The ratio improved, as 63 funds sold all Home Depot Inc shares owned while 638 reduced positions. 103 funds bought stakes while 543 increased positions. They now own 870.00 million shares or 6.34% less from 928.89 million shares in 2016Q1.
Suntrust Banks, a Georgia-based fund reported 1.27M shares. Ep Wealth Advisors holds 0.06% of its portfolio in Home Depot Inc (NYSE:HD) for 3,167 shares. Cookson Peirce & accumulated 48,303 shares or 0.92% of the stock. Goelzer Inv Mgmt accumulated 1,794 shares or 0.03% of the stock. Ibm Retirement Fund reported 163,844 shares or 0.77% of all its holdings. First Quadrant Limited Partnership Ca accumulated 1.05% or 374,300 shares. The New York-based Engineers Gate Manager Lp has invested 0.4% in Home Depot Inc (NYSE:HD). Welch & Forbes Ltd Liability Corp holds 1.72% or 441,481 shares in its portfolio. Pensionfund Dsm Netherlands holds 1.06% of its portfolio in Home Depot Inc (NYSE:HD) for 62,000 shares. Huber Capital Management Limited Liability accumulated 127,175 shares or 0.67% of the stock. First Manhattan Co accumulated 0.02% or 28,718 shares. Mark Asset reported 4,267 shares or 0.16% of all its holdings. Reik & Company Ltd Liability Corp has 0.16% invested in the company for 3,799 shares. Quadrant Mgmt Ltd has invested 2.7% of its portfolio in Home Depot Inc (NYSE:HD). U S Global Incorporated has invested 0.61% of its portfolio in Home Depot Inc (NYSE:HD).
Insider Transactions: Since May 18, 2016, the stock had 1 insider buy, and 8 sales for $41.51 million net activity. Crow Timothy M sold $6.67M worth of stock. Roseborough Teresa Wynn also sold $1.59M worth of Home Depot Inc (NYSE:HD) on Thursday, August 18. Another trade for 43,026 shares valued at $5.64 million was made by HOLIFIELD MARK on Wednesday, May 18. The insider Hewett Wayne M. bought $46,386. Menear Craig A sold $6.07 million worth of stock. TOME CAROL B had sold 97,610 shares worth $13.21 million on Monday, August 22. 10,000 Home Depot Inc (NYSE:HD) shares with value of $1.35M were sold by Decker Edward P..
The Home Depot, Inc. is a home improvement retailer. The company has a market cap of $158.59 billion. The Firm sells an assortment of building materials, home improvement products, and lawn and garden products, and provides various services. It has a 21.7 P/E ratio. The Home Depot stores serve three primary customer groups: do-it-yourself (DIY) customers, do-it-for-me (DIFM) clients and professional customers.
HD Company Profile
The Home Depot, Inc. (The Home Depot), incorporated on June 29, 1978, is a home improvement retailer. The Firm sells an assortment of building materials, home improvement products, and lawn and garden products, and provides various services. The Home Depot stores average approximately 104,000 square feet of enclosed space, with over 24,000 additional square feet of outside garden area. The Home Depot stores serve three primary customer groups: do-it-yourself (DIY) customers, do-it-for-me (DIFM) clients and professional customers. The Firm has approximately 2,270 stores located throughout the United States, including the Commonwealth of Puerto Rico and the territories of the United States Virgin Islands and Guam, Canada and Mexico.
More notable recent Home Depot Inc (NYSE:HD) news were published by: Fool.com which released: "3 Reasons Home Depot Inc. Stock Could Fall" on September 29, 2016, also Fool.com with their article: "5 Surprising Facts About Home Depot Inc You Need to Know" published on September 20, 2016, Fool.com published: "Better Buy: The Home Depot, Inc. vs. Lowe's" on September 16, 2016. More interesting news about Home Depot Inc (NYSE:HD) were released by: Fool.com and their article: "Better Buy: Wal-Mart Stores Inc. vs. Home Depot" published on September 21, 2016 as well as Fool.com's news article titled: "3 Brilliant Ways Home Depot Inc. Is Investing in the Future" with publication date: September 07, 2016.
Receive News & Ratings Via Email - Enter your email address below to receive a concise daily summary of the latest news and analysts' ratings with our FREE daily email newsletter.


text:
Description of this paper
MSSU MKRT300 Week 3 quiz 3
Question;Question 1The term _____ is used to describe retailers without traditional stores or catalogs.mom-and-popbrick-and-mortarwalled-gardenpure-play2.5 points Question 2Sandra is surfing the Web. After entering a popular site for attorneys, a separate window suddenly appears on the screen promoting a new line of legal software. This is an example of a _____ ad.bannerpop-upsearch marketingconversion2.5 points Question 3Which of the following statements about B2C e-marketing is true?B2C e-business involves online sale of services as much as physical goods.B2C transactions account for the bulk of the e-business activity volume.B2C e-marketing facilitates transactions between organizations.Service providers prefer the B2B model to B2C as there is not enough scope for service transactions in B2C e-business.2.5 points Question 4The click-through rate is a measure of the:number of clicks performed by an average user when searching for information through a search engine.number of ads served up to a user on a search engine per query.percentage of people presented with a banner ad who click on it.number of Web pages viewed by a user after clicking through an ad.2.5 points Question 5_____ is a technology that secures a Web site by encrypting information and providing authentication.SMTPHTTPSSLTCP/IP2.5 points Question 6The term _____ is used to describe a high-tech scam that uses authentic-looking e-mail or pop-up messages to get unsuspecting victims to reveal personal information.brute-force attackphishingdata harvestingshoulder surfing2.5 points Question 7_____ involves paying search engines, such as Google, a fee to make sure the company?s listing appears toward the top of the search results.Search engine optimizationPage rankingSearch marketingContextual advertising2.5 points Question 8By enabling the coordination of all promotional activities to produce a unified, customer-focused promotional message, e-marketing helps reach consumers through:personalization.interactive marketing.global reach.integrated marketing.2.5 points Question 9A _____ is a Web page anyone can edit so a reader can, in addition to asking questions or posting comments, actually make changes to the Web page.blogwikitweetNews Feed2.5 points Question 10Which of the following age groups is a typical Internet user likely to be in?11-2518-6424-3941-57
Paper#46738 | Written in 18-Jul-2015Price : $22


text:
Good Santa, Bad Santa: A Christmas Photo Gallery
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25 Best Christmas Movies of All Time
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Now Streaming: Jodorowsky's Dune, The Manchurian Candidate, and More
July 8, 2014
Weekly Ketchup: Sequels for Bad Santa and Shakespeare in Love?
December 17, 2010
Ewan McGregor to Star with Jim Carrey in I Love You Phillip Morris
December 18, 2007
Anyone Up for a "Bad Santa 2"?
February 16, 2007
RT's Top Yuletide Comedies — Christmas Countdown, Day One
December 18, 2006
Trailer Bulletin: "Live Free Or Die Hard," AKA Car Chases, Explosions, and Helicopters!
December 15, 2006
Box Office Guru Preview: Ashton vs. Ashton – This Time It's Personal
September 28, 2006
Ebertfest 2006: Festival Ends "Bad"-ly
May 3, 2006
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December 6, 2016


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OliveNation professional-quality Liquid Food Color s are fantastic for adding the most vibrant colors to your cakes, cookies, cupcakes, frostings, buttercreams, and other treats. Our food coloring hues include black, brown, Boston green, yellow, pink, red, royal blue, sky blue, orange, violet, burgundy, and teal. The possibilities our endless for our liquid food color s.
Why are our liquid food color s so good? OliveNation food colorings were developed using the highest standards. They mix evenly into batters and frostings, giving your creations consistent and uniform color. Our liquid food colors are intended for professional use, so they produce intense colors, if desired. Remember, the more food coloring you add to your recipe, the stronger the color. They are tasteless and Made in the USA.
What are some ways to use food coloring? The uses for liquid food coloring are limitless. Here are some fun ideas:
• Color white chocolate to make lollipops and other candy treats, like gumdrops.
• Add rich hues to buttercreams, fondant, whipped cream, cream cheese, and other frostings. You can even stamp fondant with food coloring for an impressive result.
• Dip candy apples.
• Transform white cakes, marshmallows, cookies, popcorn, crispy rice treats, dessert bars, and breads with a liquid food colors. You can use one color or craft a rainbow.
• Bake a beautiful red velvet cake with our red liquid food color .
• Freeze colorful homemade popsicles and ice cream with food coloring.
• Create edible "glitter" using liquid food color s and granulated sugar.
• Dye eggs.
• Bake fancy French macarons with fancy colors.
• Add a few drops of liquid food color to make party punches, sparkling water, and other beverages extra special.
Are there non-edible uses for liquid food color? Yes! You can use food coloring in many craft projects. You can make your own colorful play dough or watercolors. Turn white sand into colorful sand with liquid food color . Or, use food coloring in science projects. The list goes on an on!
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"Its an obvious choice, but the..." Singapore Favorite Tip by heathpj
Singapore General: 441 reviews and 444 photos
Favorite thing: Its an obvious choice, but the shopping is absolutely amazing down orchard road, and shouldnt, and i doubt whether it would be missed by any traveller to singapore. Besides that, the local distinct cultral centres of Chinatown and Little India are great for traditional meals, clothing and shopping. For something a little different and not so hectic, another smaller area which is becomming more and more popular with both locals and tourists is Holland Village. It is the suburb where i lived and is a common place for expats to live because of the townhousing, exectutive apartments and proximity to central points of Singapore. It is worth a visit to explore the food centres and the Holland Village shopping centre, which houses alot of traditional arts and crafts, woodworks, sillks, and jewellery. There are countless coffee shops and pubs to enjoy a nice drink and break from the humdidity. It is approximatly a 10 mintue ride from the Orchard road, and along the way are the beautiful botanical gardens. The picture i have included looks down Lor Liput in Holland Village on a busy Saturday.
Fondest memory: By living there for awhile, the fondest memories are of course the friends i made, the local idiosyncrasies of the local hawker centres are not to be missed.
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- Foundation
- Ecology
How organic farming preserves natural habitats, boosts ecological diversity, increases soil fertility and generates stable yield.
- Education
How our schools offer new opportunities to underprivileged children.
- Development
How fair-trade organic cotton secures sustainable livelihoods for farmer families in India and Tanzania.
- Heal
How effective measures make a significant difference in the state of health in rural areas.
- Work
How we support small farmers in upgrading their farms, and promote community-building.


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2 Bedrooms Semi Detached House for sale
Tippets Knowe Road, Winchburgh, West Lothian, EH52
Housesimple is proud to present this 2 bedroom, semi-detached house in winchburgh. this property benefits from 0 receptions and 1 bathroom, gas heating, all double-glazed windows,…
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Moving from one home to the next is a tiring, lengthy process, especially if you're unprepared for the task. With proper planning you greatly reduce the amount of stress on your shoulders and make relocating something that is far more enjoyable. Here are five tips for a smooth move to get you started.
- Start Early
Planning ahead for the move is important, and the earlier that you start planning, the better. Make lists of inventory; purchase packing supplies lodi and boxes, and get in gear! Trying to do it all at once isn't the ideal solution to a difficult job.
- Organize
An organized move is yet another tip that makes it much easier to get to your new home without mounds of stress on your shoulders. Be sure that you label boxes, don't pack them to full, and get a storage unit if it is needed.
- Work with a Moving Company
Moving companies are available to assist with your move for various fees. They have all of the tools and equipment needed, along with manpower and the muscle, to get the job done with ease. If may be worthwhile to look into the services offered by a moving company.
- Protect your Valuables
Nothing is worse than realizing the things that you treasure the most have been damaged during the move. Take the precaution before you begin and enjoy a worry-free move. You can find many different supplies to keep most anything protected. It is worth the purchase.
- Check the House again
You might be surprised how easy it is to leave things behind in a move –even when you think you've got it all. It never hurts to go back and give your house a second look. You might find something that you didn't want to leave behind!


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SPV launched their series of archival Ike & Tina Turner collections with this double-disc set, which curiously enough is the least interesting installment in the program so far. The Archive Series, Vols. 1 & 2: Hits and Classics is devoted to songs already familiar to casual listeners, but the only real-deal Ike & Tina hits included on this set are "It's Gonna Work Out Fine," "Nutbush City Limits," "Proud Mary," and "River Deep, Mountain High" (the latter two each appearing twice), while nearly everything else is a cover of a tune associated with another artist.
Benny Carter's MusicMasters catalogue turned up some fine sessions in which colleagues included Clark Terry, Hank Jones, and Doc Cheatham, among a raft of musicians - for the stellar singers, see the end of this review. The recordings, made in various locations, span the years 1990-95 and reveal the altoist seemingly unruffled by the reach of Time, still spinning some sublime and harmonically darting lines as if for the first time.
This boxed set of four CDs recorded between 1987 and 1989 illustrates Benny Carter's versatility performing with four different groups. He was already aged 80 when he recorded the first of these albums, yet there is no sign of ageing. Indeed, Benny stayed alive and active until he was 95. From the very first track, the listener is struck by Carter's pure, mellow sound, putting him in contention with Johnny Hodges and Willie Smith as one of the three altoists in jazz with the sweetest tone. This CD also exhibits Benny as a composer, since he wrote all eleven tunes. Dizzy Gillespie makes guest appearances on three tracks, playing with restraint and harmonizing well with Carter.
Simply the Best is the first greatest hits compilation by Tina Turner and was released on October 22, 1991. The album includes Turner's most popular hits since her comeback in the early-mid 1980s. It also includes three new songs that were previously unreleased; "Love Thing" (UK Airplay #13), "I Want You Near Me" (#22 UK), and "Way of the World" (UK Airplay #6 and UK #13) as well as a re-recorded dance version of Turner's classic "Nutbush City Limits", all of which were also issued as singles in 1991 and 1992…


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Roger Federer will cut exhibition matches from his 2009 schedule as he pursues Pete Sampras' record of 14 Grand Slam singles titles, his agent said Sunday.
Federer and Sampras played three exhibition matches across Asia last November and again in New York City last March.
Such commitments won't be repeated in 2009, agent Tony Godsick told The Associated Press. "Roger will only play a schedule that works for him physically," Godsick said after Federer won his hometown tournament at the Swiss Indoors on Sunday.


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Outside our building is a bush that smells like cheesy shit. Seriously. Either that or it's something IN the bush. Whatever it is, it's not right. Ewwwwwwww.
Oh well. At least we don't live on the ground floor. Here I am floating high above the hot reek of bins and Stinkbush, like Lady Muck. Hooray!


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Wyoming Uranium Mining Company Layoffs
The jobs affected will be at the company's two offices, in Casper and Littleton-Colorado, and at its Lost Creek Mine in south-central Wyoming.
The jobs affected will be at the company's two offices, in Casper and Littleton-Colorado, and at its Lost Creek Mine in south-central Wyoming.
The company operates the Smith Ranch-Highland mine near Glenrock and the North Butte mine south of Gillette.
Officials say residents shouldn't be alarmed, but noted that infants, the elderly and pregnant women could be susceptible to increased risks.
A legislative committee has endorsed the idea of Wyoming taking over sole regulation of uranium mining in the state.
Under the Lummis language, a ten percent drop in the price of uranium would invalidate the Department's standing uranium transfer authority.
A uranium company has purchased two mines that have been idle since the 1990s and has plans to start them up again.
A uranium company has secured a $20 million state bond to begin production at a mine in northeast Wyoming. Kevin Koile reports. Governor Matt Mead has announced a partnership to create new maps and a clearinghouse of geographic information system data about Wyoming...
The State of Wyoming has invested $34 million in an in-situ uranium mine in Sweetwater County. The Wyoming Entrepreur will host a webinar Tuesday afternoon...
A federal judge has ruled against an environmental group's challenge to an in-situ uranium mine that started production last month in Sweetwater County.
Northern Wyoming reservoirs are poised for runoff. Amy Richards has details. Casper's Ablation Technologies has entered an agreement to manufacture and operate technology it has to developed to recover uranium. Business Reporter Sharon Fain has a report. Click past jump to listen to Wyoming Radio News.


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Opening for Import/export Executive in New Delhi ( 2 - 3 yrs)
Space Consultant
RS3,00,000 To 3,50,000Delhi
Job Position :- Import/Export Executive. Qualification :- Graduation. Experience :- 2-3Years Of Sales. Job Description :- Candidate Will Have To Handle Import/Export And Sales Activities In The Company.Its A Sitting Job. Salary :- 25-3...
Key Skills : good communication skills,managerial skills,documentation executive,import associate,export import executive
Senior Accountant ( 3 - 10 yrs)
G T Fruitech Pvt. Ltd
RS2,50,000 To 3,50,000North Delhi, Delhi
To carry out the following with due resposibility : 1. Accounts 2. Export documentation 3. Communicating with international customers..
Key Skills : accountant,account,export import management,export documentation executive,export documentation...
Export Documentation Incharge ( 2 - 5 yrs)
Essjay Placement
RS2,00,000 To 3,00,000West Delhi, Delhi
Making Invoice & Packing List as per Purchase Order pre. Shipment Docs to Cha or Freight Forwarder dsr to Buyer order Packing Material, Stickers & Labels as per Buyer Requirement chart (weekly/fortnightly/monthly...
Key Skills : export documentation incharge,export import executive,export
Mitsui Chemicals India
RS2,00,000 To 3,50,000Delhi
- Basic understanding on \"Import & Export shipment operations\" & \"logistics\" (Sea & Air)I - Import & Export documentation, Sales invoice creation & also have Commercial knowledge (CST & VAT) - Follow ups with CHA/ vendors - Preparing High Sea ...
Key Skills : scm operations import coordination cha high sea sales documentation,scm operations,import coordination,cha high sea sales documentation,sales...


text: Hi all. Is there a way that I could add OpenSSH to the redsn0w folder so I could SSH into my iPod? I have no wifi at my mothers house and I had to restore my iPod Touch to factory settings. I want to re-jailbreak and be able to SSH. Some help would be awesome. Please Register or Log in to view images Sorry if this is a stupid question Please Register or Log in to view images


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Download apps, toolboxes, and other File Exchange content using Add-On Explorer in MATLAB.
Join the 15-year community celebration.
Play games and win prizes!
Rate this file 11 Downloads (last 30 days) File Size: 1.42 KB File ID: #21291 Version: 1.0
Demonstration of Gibbs' Phenomenon
02 Sep 2008 (Updated 02 Sep 2008)
Demo on Gibbs' phenomenon


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Latest Camera Reviews
Olympus OM-D E-M1 Mark II Review
Panasonic Lumix DMC-FZ2000 Review
Panasonic Lumix DMC-LX15 Review
Mac users, we're pleased to announce Macphun's all-in-one photo editor Luminar is now available for purchase with special launch pricing. (Existing Macphun customers get a further discount.)
We rated Luminar as "Highly Recommended", and you can now visit the Luminar web site to try it for free.
The Perfect Photo: 71 Tips from the Top by Elin Rantakrans and Tobias Hagberg provides beginners with a wide range of practical tips that cover composition, image capture and editing. Illustrated with inspiring images throughout, this pocket-sized book is published by Rocky Nook and available for $19.95 / £15.50 / €16.00.


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Harvey recommended DOOM. a month ago
DOOM is a modern day release in a very old franchise, a first person shooter that focuses on just that, shooting and killing. It utilizes fast paced action with precise controls in order to present a new arena style shooter.
Pro Powerful and customizable weapon selections
You start the game with a pistol, but almost immediately start getting new weapons such as the shotgun. During the gameplay new modifications will be unlocked for each weapon, which allows for a good set of customizability in order to fit with ones playstyle. Each weapon has two different mods that
Pro Longevity thanks to a level editor
There is a level editor included in the game meaning anyone can design their own levels. What is even better is that these levels can be shared online. This way there will be an endless amount of levels to play, making for a lot of longevity of play for those interested.
Pro Fun hidden secrets
There are quite a few easter eggs and hidden secrets in the game, such as old school Doom 95 levels, a Commander Keen skull, a Terminator 2 animation or a hidden Halo toy that the player will fist bump. This give incentive to search out all areas of the game as you never know what you will find.
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Pro Lets you roleplay matrix-like battles
The coolest thing about this mechanic is it essentially lets you role play matrix-like battles with you dodging bullets, slicing bullets out of mid-air with a katana and an assortment of other badass things to do.
Pro Awesome time-based mechanic
In Superhot time only goes forward when you move. This turns the gameplay into something closer to a puzzle game as you need to be very calculated with every move you make.
Pro Minimalistic yet beneficial art style
The art style in the game is very cool and minimalistic while actually serving to make the game easier to understand and play. The gameplay in Superhot relies on you being able to react properly to your environment, and the art choices make it really easy to understand what is going on around you.
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Pro Plays at 1080p and 60fps
The majority of the game holds at a steady 60fps while being played in 1080p or slightly less. This makes for a visually appealing game thanks to the solid framerate in what is often full HD.
Con Drops resolution in certain places
Certain points of the game may drop the resolution down to 1760x1080 (from 1920x1080) in order to keep the gameplay running at 60 frames per second, while this does not happen often, it does happen.
Pro Well written and acted
The story in the game is well fleshed out. It is a fictional story about if the Nazis took over the world after WWII, which is not a new premise, but has so many little touches that really create an immersive story that the player cares about. This is where the animation and voice acting of the ga...
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Borderlands: The Pre-Sequel is a co-op first person shooter action adventure game that costs $59.99.
Con Extremely poor writing
The writing in Borderlands: The Pre-Sequel is very poor, the jokes often fall flat with some of the writing sometimes giving an awkward feeling. It is almost as if there is an intentional randomness to it, but even that does not appear to be the case as there is quite a lot of social driven issues...
Pro Low gravity effects
The new low gravity effects work quite well giving the player more of a chance to put distance between them and their targets, which makes sniping a lot more viable than in previous games.
Pro End game takes advantage of all players skills and weapons
The end game is the best part of Borderlands: The Pre-Sequel as it takes advantage of requiring the player to use a lot of reflex while utilizing all of their skills and weapons. It is quite a balancing act and when pulled off it very exhilarating.
Far Cry 4 is an open-world first person shooter adventure game created by Ubisoft. The gameplay consists of mainly first person shooter action, where the player is tasked with going to different areas of an open-world map in order to shoot particular people to complete a task. Players can slowly upgrade their equipment/weapons through what they earn in completing certain tasks. This is repeated until the player finally finishes the game.
Pro Adventure aspects add to what would be a stale FPS
Being able to scale cliffs, hunt and trap animals, and use ones environment as a weapon against enemies adds to the basics of first person shooting making for a fun adventure game on top of a slick FPS.
Pro Options in play due to creativity
There are so many ways to tackle a situation that makes this game what it is. In one instance you could lure an animal towards enemies in order to kill them, or in another you could run everyone over with a truck. Even better is that explosives can be attached to things, even vehicles, so you can...
Con Environment feels too familiar
While Farcry 1-3 all had different locales that had their own styles, 4 looks much like 3 and is not that much of a departure. For those looking for a different experience it is not going to be found in 4 sadly.
Far Cry 4 is an open-world first person shooter adventure game created by Ubisoft. The gameplay consists of mainly first person shooter action, where the player is tasked with going to different areas of an open-world map in order to shoot particular people to complete a task. Players can slowly upgrade their equipment/weapons through what they earn in completing certain tasks. This is repeated until the player finally finishes the game.
Pro Inspired by Hexen and Doom
Ziggurat is heavily inspired by the classic PC games Hexen and Doom, making for a current gen refresh.
Pro Procedurally generated levels and random weapons upon start
Ziggurat has large procedurally generated levels where the player start out with a different weapon each time, making for fresh and different experience every time a game is played.
Do you recommend this?
PlanetSide 2 is a massive multiplayer online shooter that is free to play.
Pro User selectable respawn points
Users can select where they want to respawn after death. There are even vehicles that provide new spawn points on the map that players can drive and leave. This creates a great element of strategy on where to place spawn points when attacking certain targets.
Pro Open world MMO-FPS with huge persistent battles between 3 factions
Three factions are in constant battle for points on a map, with the goal of getting the most pieces on the map or the whole thing.
Con Pay to win
PlanetSide 2 has pay to win mechanics meant to coerce players into paying for equipment to avoid the extremely long grind it takes to earn anything in game. A brand new player with a deep wallet can customize their gear to their prefered playstyle giving them an advantage over those that opt not to
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Insurgency is a realistic first person shooter based on a popular Source mod.
Pro Steam VoIP support
Insurgency has Steam integration that allows for easy VoIP communication.
Pro Everyone has a different class
When teams are set up the game does not allow multiple people to have the same class chosen for their character which makes for a great way to ensure teams are not imbalanced.
Con Hard to get in
Even with experience in other fps games poor maps knowledge (they are quite complex) and tactical approach require quite a few hours of learning the game mechanics before you start having actual fun
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Metacritic 82/100. Steam: 98%. May 30, 2013.
Pro Each team requires vastly different playstyles
Due to each side having different skills it will make for different tactics that need used depending on the team on is on. This makes for a great way to switch up the gameplay without having to leave the game.
Con Can take a commitment to get used to the mechanics and get good
With the precision needed for shooting in the game as well as needing to learn the ins and outs of the skillful mechanics it may take a good while before one can get fully comfortable with the game, which may frustrate some as there will be a time commitment.
Pro Great level design
All maps are quite different from each other and feature good design of the defend and attack elements. This makes for good p=balance that is often not found in many multiplayer games.
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Pro Over the top
The game's artstyle, theme, narration, enemies and even weapon reload animations are satirical of over-the-top 80's style action movies. The game is named after T-Rex-looking dragons that emit neon light.
Pro Solid gameplay
The gameplay itself is of course drenched in an over-the-top 80's sauce, but underneath that lies the solid, trusted gameplay mechanics of Far Cry 3.