15698378
A Binary Decision Tree Implementation of a Boosted Strong Classifier
Viola and Jones [1] proposed the influential rapid object detection algorithm. They used AdaBoost to select from a large pool a set of simple features and constructed a strong classifier of the form {∑jαjhj(x) ≥ θ} where each hj(x) is a binary weak classifier based on a simple feature. In this paper, we construct, using statistical detection theory, a binary decision tree from the strong classifier of the above form. Each node of the decision tree is just a weak classifier and the knowledge of the coefficients αjis no longer needed. Also, the binary tree has a lot of early exits. As a result, we achieve an automatic speedup that always makes the rapid Viola and Jones algorithm rapider.
15470334
Probabilistic recognition of human faces from video
Recognition of human faces using a gallery of still or video images and a probe set of videos is systematically investigated using a probabilistic framework. In still-to-video recognition, where the gallery consists of still images, a time series state space model is proposed to fuse temporal information in a probe video, which simultaneously characterizes the kinematics and identity using a motion vector and an identity variable, respectively. The joint posterior distribution of the motion vector and the identity variable is estimated at each time instant and then propagated to the next time instant, Marginalization over the motion vector yields a robust estimate of the posterior distribution of the identity variable. A computationally efficient sequential importance sampling (SIS) algorithm is developed to estimate the posterior distribution. Empirical results demonstrate that, due to the propagation of the identity variable over time, a degeneracy in posterior probability of the identity variable is achieved to give improved recognition. The gallery is generalized to videos in order to realize video-to-video recognition. An exemplar-based learning strategy is adopted to automatically select video representatives from the gallery, serving as mixture centers in an updated likelihood measure. The SIS algorithm is applied to approximate the posterior distribution of the motion vector, the identity variable, and the exemplar index, whose marginal distribution of the identity variable produces the recognition result. The model formulation is very general and it allows a variety of image representations and transformations. Experimental results using images/videos collected at UMD, NIST/USF, and CMU with pose/illumination variations illustrate the effectiveness of this approach for both still-to-video and video-to-video scenarios with appropriate model choices.
8965145
A robust algorithm for probabilistic human recognition from video
Human recognition from video requires solving the two tasks, recognition and tracking, simultaneously. This leads to a parameterized time series state space model, representing both motion and identity of the human. Sequential Monte Carlo (SMC) algorithms, like Condensation, can be developed to offer numerical solutions to this model. However in outdoor environments, the solution is more likely to diverge from the foreground, causing failures in both recognition and tracking. In this paper we propose an approach for tackling this problem by incorporating the constraint of temporal continuity in the observations. Experimental results demonstrate improvements over its Condensation counterpart.
8505547
Face recognition from video: a CONDENSATION approach
The aim of this work is to investigate how to exploit the temporal information in a video sequence for the task of face recognition. Following the approach in (Li and Chellappa, 2000), we propose a probabilistic model parameterized by a tracking state vector and a recognizing identity variable, simultaneously characterizing the kinematics and identity of humans. We then invoke a CONDENSATION (Isard and Blake, 1996) approach to provide a numerical solution to the model. Once the joint posterior distribution of the state vector and the identity variable is estimated, we marginalize it over the state vector to yield a robust estimate of the posterior distribution of the identity variable. Due to the propagation of identity and dynamics, a degeneracy in the posterior distribution of the identity variable is achieved to give improved recognition. This evolving behavior is characterized using changes in entropy. The effectiveness of this approach is illustrated using experimental results on low-resolution video data.
41942332
Exemplar-Based Face Recognition from Video
A new exemplar-based probabilistic approach for face recognition in video sequences is presented. The approach has two stages: First, Exemplars, which are selected representatives from the raw video, are automatically extracted from gallery videos. The exemplars are used to summarize the gallery video information. In the second part, exemplars are then used as centers for probabilistic mixture distributions for the tracking and recognition process. A particle method is used to compute the posteriori probabilities. Probabilistic methods are attractive in this context as they allow a systematic handling of uncertainty and an elegant way for fusing temporal information.Contrary to some previous video-based approaches, our approach is not limited to a certain image representation. It rather enhances known ones, such as the PCA, with temporal fusion and uncertainty handling. Experiments demonstrate the effectiveness of each of the two stages. We tested this approach on more than 100 training and testing sequences, with 25 different individuals.
60706602
Multiple-exemplar discriminant analysis for face recognition
Face recognition is characteristically different from regular pattern recognition and, therefore, requires a different discriminant analysis other than linear discriminant analysis(LDA). LDA is a single-exemplar method in the sense that each class during classification is represented by a single exemplar, i.e., the sample mean of the class. We present a multiple-exemplar discriminant analysis (MEDA) where each class is represented using several exemplars or even the whole available sample set. The proposed approach produces improved classification results when tested on a subset of FERET database where LDA is ineffective.
815725
Virtual Execution Environments: Support and Tools
In today's dynamic computing environments, the available resources and even underlying computation engine can change during the execution of a program. Additionally, current trends in software development favor the flexibility and cost-effectiveness of dynamically loaded components and libraries. Because of these trends, there has been increased research interest in virtual execution environments (VEEs) for delivering adaptable software suitable for today's rapidly changing, heterogeneous computing environments. In this project, we have been investigating tools and techniques to support implementation of VEEs using software dynamic translation (SDT). This paper highlights some of our recent results. One significant result is that we have developed novel translation techniques that reduce the memory and runtime overhead of SDT to negligible levels. We have also developed innovative debugging and instrumentation tools for SDT-based software environments. Together, these results make SDT-based systems viable for solving a wide range of pressing problems. The paper concludes with a discussion of how SDT may offer a solution to one such problem-inherent process variation in emerging chip multiprocessors.
12615212
Finite locally-quasiprimitive graphs
A finite graph is said to be locally-quasiprimitive relative to a subgroup G of automorphisms if, for all vertices α, the stabiliser in G of α is quasiprimitive on the set of vertices adjacent to α. (A permutation group is said to be quasiprimitive if all of its non-trivial normal subgroups are transitive.) The graph theoretic condition of local quasiprimitivity is strictly weaker than the conditions of local primitivity and 2-arc transitivity which have been studied previously. It is shown that the family of locally-quasiprimitive graphs is closed under the formation of a certain kind of quotient graph, called a normal quotient, induced by a normal subgroup. Moreover, a locally-quasiprimitive graph is proved to be a multicover of each of its normal quotients. Thus finite locally-quasiprimitive graphs which are minimal in the sense that they have no non-trivial proper normal quotients form an important sub-family, since each finite locally-quasiprimitive graph has at least one such graph as a normal quotient. These minimal graphs in the family are called "basic" locally-quasiprimitive graphs, and their structure is analysed. The process of constructing locally-quasiprimitive graphs with a given locally-quasiprimitive graph Σ as a normal quotient is then considered. It turns out that this can be viewed as a problem of constructing covering graphs of certain multigraphs associated with Σ. Further, it is shown that, under certain conditions, a locally-quasiprimitive graph can be reconstructed from knowledge of two of its normal quotients. Finally a series of open problems is presented.
14537383
Constructing a Class of Symmetric Graphs
We find a natural construction of a large class of symmetric graphs from point- and block-transitive 1-designs. The graphs in this class can be characterized as G -symmetric graphs whose vertex sets admit a G -invariant partition B of block size at least 3 such that, for any two blocks B, C of B, either there is no edge between B and C, or there exists only one vertex in B not adjacent to any vertex inC . The special case where the quotient graph ?Bof ? relative to B is a complete graph occurs if and only if the 1-design needed in the construction is a G -doubly transitive and G -block-transitive 2-design, and in this case we give an explicit classification of ? when G is a doubly transitive projective group or an affine group containing the affine general group. Examples of such graphs include cross ratio graphs studied recently by Gardiner, Praeger and Zhou and some other graphs with vertices the (point, line)-flags of the projective or affine geometry.
151575
Matroid tree graphs and interpolation theorems
Using the Hamiltonicity of matroid tree graphs we give a new proof for an interpolation theorem of Barefoot (1984) and other related results. From the proof we refine a general approach for dealing with interpolation problems of graphs.
13207643
Towards Modelling The Internet Topology - The Interactive Growth Model
The Internet topology at the Autonomous Systems level (AS graph) has a power-law degree distribution and a tier structure. In this paper, we introduce the Interactive Growth (IG) model based on the joint growth of new nodes and new links. This simple and dynamic model compares favorable with other Internet power-law topology generators because it not only closely resembles the degree distribution of the AS graph, but also accurately matches the hierarchical structure, which is measured by the recently reported rich-club phenomenon.