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Decentralized multiple target tracking using netted collaborative autonomous trackers

Decentralized multiple target tracking using netted collabor...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Ting Yu Ying Wu Department of Electrical & Computer Engineering Northwestern University Evanston IL USA

ISBN: (纸本)0769523722

This paper presents a decentralized approach to multiple target tracking. The novelty of this approach lies in the use of a set of autonomous while collaborative trackers to overcome the tracker coalescence problem with linear complexity. In this approach, the individual trackers are autonomous in the sense that they can select targets to track and evaluate themselves, and they are also collaborative since they need to compete for the targets against those trackers that are close to them through communication. The theoretical foundation of this new approach is based on the variational analysis of a Markov network that reveals the collaborative mechanism through fixed point iteration among these trackers and the existence of the equilibriums. In addition, a trained object detector is incorporated to help sense the potential newly appearing targets in the dynamic scene. Experimental results on challenging video sequences demonstrate the effectiveness and efficiency of the proposed method.

关键词： Target tracking Collaboration computer networks Distributed computing Markov random fields Object detection Detectors Layout Video sequences State-space methods

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Optimal point correspondence through the use of rank constraints

Optimal point correspondence through the use of rank constra...

引用

conference on computer vision and pattern recognition (cvpr)

作者： R. Oliveira J. Costeira J. Xavier Instituto Superior Técnico Instituto de Sistemas e Robótica Lisboa Portugal

We propose a solution to the n-frame correspondence problem under the factorization framework. During the matching process, our algorithm takes explicitly into account the geometrical constraints associated to the reconstruction process. To this end, a rank constraint is imposed on the measurement matrix. Since our method relies solely on geometric constraints, it is not dependent on corners as image features and can consequently match generic points (e.g. contours). Outlier rejection is integrated as a part of the actual matching process. In general the problem is formulated as combinatorial, but we develop a method, which can provide a solution with a low computational complexity. Because of this, our algorithm is able to handle high-dimensional matching problems that are common in real-life applications.

关键词： Image reconstruction pattern matching Cost function Photometry Computational complexity Shape Stereo image processing Algorithm design and analysis Design optimization Performance gain

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An Experimental Comparison of Three Guiding Principles for the Detection Salient Image Locations: Stability, Complexity, and Discrimination

An Experimental Comparison of Three Guiding Principles for t...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Dashan Gao N. Vasconcelos Department of Electrical and Computer Engineering University of California San Diego USA

We present an experimental comparison of the performance of representative saliency detectors from three guiding principles for the detection of salient image locations: locations of maximum stability with respect to image transformations, locations of greatest image complexity, and most discriminant locations. It is shown that discriminant saliency performs better in terms of 1) capturing relevant information for classification, 2) being more robust to image clutter, and 3) exhibiting greater stability to image transformations associated with variations of 3D object pose. We then investigate the dependence of discriminant saliency on the underlying set of candidate discriminant features, by comparing the performance achieved with three popular feature sets: the discrete cosine transform, a Gabor, and a Haar wavelet decomposition. It is show that, even though different feature sets produce equivalent results, there may be advantages in considering features explicitly learned from examples of the image classes of interest.

关键词： Detectors Image edge detection Robust stability Machine vision computer vision Biological system modeling Discrete cosine transforms Discrete wavelet transforms Layout Autocorrelation

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A Time-Efficient Cascade for Real-Time Object Detection: With applications for the visually impaired

A Time-Efficient Cascade for Real-Time Object Detection: Wit...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Xiangrong Chen A.L. Yuille Department of Statistics University of California Los Angeles CA USA

Real-time object detection is essential for many computer vision applications. Many rapid detection algorithms are based on using cascades of tests. But existing design criteria for cascades either ignore the time complexity of the tests or make over-simplified assumptions about them. This paper gives a criterion for designing a time-efficient cascade that explicitly takes into account the time complexity of tests (as evaluated by computer run time) including the time for pre-processing. We design a greedy algorithm to minimize this criterion (noting that the full problem is NP-complete). Finally, we illustrate our method on the task of text detection in city scenes. This gives a text detection algorithm that runs at 0.025 seconds per 320×240 image, which is equivalent to 40 frames per second. This is a speed up factor of 2.5 compared to our previous text detector. It gives a realtime system which can be used for applications to help the blind and visually impaired.

关键词： Object detection Testing Application software Detection algorithms computer vision Algorithm design and analysis Greedy algorithms Cities and towns Layout Detectors

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Strategies and Benefits of Fusion of 2D and 3D Face recognition

Strategies and Benefits of Fusion of 2D and 3D Face Recognit...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： M. Husken M. Brauckmann S. Gehlen C. Von der Malsburg Viisage Technology AG Bochum Germany Institut für Neuroinformatik Ruhr Universität Bochum Bochum Germany

The extension of 2D image-based face recognition methods with respect to 3D shape information and the fusion of both modalities is one of the main topics in the recent development of facial recognition. In this paper we discuss different strategies and their expected benefit for the fusion of 2D and 3D face recognition. The face recognition grand challenge (FRGC) provides for the first time ever a public benchmark dataset of a suitable size to evaluate the accuracy of both 2D and 3D face recognition. We use this benchmark to evaluate hierarchical graph matching (HGM), an universal approach to 2D and 3D face recognition, and demonstrate the benefit of different fusion strategies. The results show that HGM yields the best results presented at the recent FRGC workshop, that 2D face recognition is significantly more accurate than 3D face recognition and that the fusion of both modalities leads to a further improvement of the 2D results.

关键词： Face recognition Shape Face detection pattern recognition Image databases Gray-scale Color computer vision Data security Access control

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Nonparametric subspace analysis for face recognition

Nonparametric subspace analysis for face recognition

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conference on computer vision and pattern recognition (cvpr)

作者： Zhifeng Li Wei Liu Dahua Lin Xiaoou Tang Department of Information Engineering Chinese University of Hong Kong Sha Tin Hong Kong China Microsoft Research Asia Beijing China

ISBN: (纸本)0769523722

Linear discriminant analysis (LDA) is a popular face recognition technique. However, an inherent problem with this technique stems from the parametric nature of the scatter matrix, in which the sample distribution in each class is assumed to be normal distribution. So it tends to suffer in the case of non-normal distribution. In this paper a nonparametric scatter matrix is defined to replace the traditional parametric scatter matrix in order to overcome this problem. Two kinds of nonparametric subspace analysis (NSA): PNSA and NNSA are proposed for face recognition. The former is based on the principal space of intra-personal scatter matrix, while the latter is based on the null space. In addition, based on the complementary nature of PNSA and NNSA, we further develop a dual NSA-based classifier framework using Gabor images to further improve the recognition performance. Experiments achieve near perfect recognition accuracy (99.7%) on the XM2VTS database.

关键词： Face recognition Scattering Linear discriminant analysis Null space Gaussian distribution Spatial databases Feature extraction Asia Image recognition Image databases

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Automatic face recognition for film character retrieval in feature-length films

Automatic face recognition for film character retrieval in f...

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conference on computer vision and pattern recognition (cvpr)

作者： O. Arandjelovic A. Zisserman Engineering Department University of Oxford UK

The objective of this work is to recognize all the frontal faces of a character in the closed world of a movie or situation comedy, given a small number of query faces. This is challenging because faces in a feature-length film are relatively uncontrolled with a wide variability of scale, pose, illumination, and expressions, and also may be partially occluded. We develop a recognition method based on a cascade of processing steps that normalize for the effects of the changing imaging environment. In particular there are three areas of novelty: (i) we suppress the background surrounding the face, enabling the maximum area of the face to be retained for recognition rather than a subset; (ii) we include a pose refinement step to optimize the registration between the test image and face exemplar; and (iii) we use robust distance to a sub-space to allow for partial occlusion and expression change. The method is applied and evaluated on several feature length films. It is demonstrated that high recall rates (over 92%) can be achieved whilst maintaining good precision (over 93%).

关键词： Face recognition Image retrieval Face detection Lighting Image recognition Content based retrieval Eyes Character recognition Motion pictures Testing

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Audio-visual affect recognition through multi-stream fused HMM for HCI

Audio-visual affect recognition through multi-stream fused H...

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conference on computer vision and pattern recognition (cvpr)

作者： Z. Zeng J. Tu B. Pianfetti M. Liu T. Zhang Z. Zhang T.S. Huang S. Levinson University of Illinois Urbana-Champaign USA

Advances in computer processing power and emerging algorithms are allowing new ways of envisioning human computer interaction. This paper focuses on the development of a computing algorithm that uses audio and visual sensors to detect and track a user's affective state to aid computer decision making. Using our multi-stream fused hidden Markov model (MFHMM), we analyzed coupled audio and visual streams to detect 11 cognitive/emotive states. The MFHMM allows the building of an optimal connection among multiple streams according to the maximum entropy principle and the maximum mutual information criterion. Person-independent experimental results from 20 subjects in 660 sequences show that the MFHMM approach performs with an accuracy of 80.61% which outperforms face-only HMM, pitch-only HMM, energy-only HMM, and independent HMM fusion.

关键词： Hidden Markov models Human computer interaction Streaming media Testing Decision making Entropy Mutual information Training data Coupled mode analysis Application software

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Efficient nearest neighbor classification using a cascade of approximate similarity measures

Efficient nearest neighbor classification using a cascade of...

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conference on computer vision and pattern recognition (cvpr)

作者： V. Athitsos J. Alon S. Sclaroff Computer Science Department Boston University Boston MA USA

This paper proposes a method for efficient nearest neighbor classification in non-Euclidean spaces with computationally expensive similarity/distance measures. Efficient approximations of such measures are obtained using the BoostMap algorithm, which produces embeddings into a real vector space. A modification to the BoostMap algorithm is proposed, which uses an optimization cost that is more appropriate when our goal is classification accuracy as opposed to nearest neighbor retrieval accuracy. Using the modified algorithm, multiple approximate nearest neighbor classifiers are obtained, that provide a wide range of trade-offs between accuracy and efficiency. The approximations are automatically combined to form a cascade classifier, which applies the slower and more accurate approximations only to the hardest cases. The proposed method is experimentally evaluated in the domain of handwritten digit recognition using shape context matching. Results on the MNIST database indicate that a speed-up of two to three orders of magnitude is gained over brute force search, with minimal losses in classification accuracy.

关键词： Nearest neighbor searches Shape measurement Image databases Testing Extraterrestrial measurements Cost function Handwriting recognition Error analysis computer science Optical computing

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Geo-consistency for wide multi-camera stereo

Geo-consistency for wide multi-camera stereo

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conference on computer vision and pattern recognition (cvpr)

作者： M.-A. Drouin M. Trudeau S. Roy DIRO Université de Montreal Canada

This paper presents a new model to overcome the occlusion problems coming from wide baseline multiple camera stereo. Rather than explicitly modeling occlusions in the matching cost function, it detects occlusions in the depth map obtained from regular efficient stereo matching algorithms. Occlusions are detected as inconsistencies of the depth map by computing the visibility of the map as it is reprojected into each camera. Our approach has the particularity of not discriminating between occluders and occludees. The matching cost function is modified according to the detected occlusions by removing the offending cameras from the computation of the matching cost. The algorithm gradually modifies the matching cost function according to the history of inconsistencies in the depth map, until convergence. While two graph-theoretic stereo algorithms are used in our experiments, our framework is general enough to be applied to many others. The validity of our framework is demonstrated using real imagery with different baselines.

关键词： Cameras Cost function Iterative algorithms Layout Stereo vision History Convergence Stereo image processing Image reconstruction Photometry

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