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Model selection within a bayesian approach to extraction of walker motion

Model selection within a bayesian approach to extraction of ...

引用

2006 conference on computer vision and pattern recognition workshops

作者： Ziheng, Zhou Damper, Robert I. Prügel-Bennett, Adam Research Group School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom

ISBN: (纸本)0769526462

Extracting articulated motion of walking people in image sequences remains a challenge, particularly when we take into account the changes caused by carried objects or the severe motion occlusions by clothing (e.g., a long skirt, a trench coat, etc). In this paper, we propose a Bayesian framework capable of handling such uncertainties by exploiting our strong prior knowledge of how humans walk. In this work, the strong prior is built from a simple articulated model, which can be easily modified to cater for situations such as walkers wearing clothing that obscures the limbs. A model selection process is built into the framework to determine the body configuration of the walker in the given sequence automatically. The statistics of the parameters describing a basic walker are learned from data and the Bayesian framework then allows us to 'bootstrap' to accurate motion extraction on the images of walkers with extra body configurations. We demonstrate our approach on the data of walkers with rucksacks, skirts and trench coats. Results are quantified in terms of average pixel error between automatically extracted body points and corresponding points labelled by hand. © 2006 ieee.

关键词： Gesture recognition

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Robust multi-pedestrian tracking in thermal-visible surveillance videos

Robust multi-pedestrian tracking in thermal-visible surveill...

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2006 conference on computer vision and pattern recognition workshops

作者： Leykin, Alex Hammoud, Riad Indiana University Department of Computer Science Bloomington IN Delphi Corporation Delphi Electronics and Safety World Headquarters IN United States

ISBN: (纸本)0769526462

In this paper we introduce a system to track pedestrians using a combined input from RGB and thermal cameras. Two major contributions are presented here. First is the novel model of the scene background where each pixel is represented as a multi-modal distribution with the changing number of modalities for both color and thermal input. We demonstrate how to eliminate the influence of shadows with this type of fusion. Second, based on our background model we introduce a pedestrian tracker designed as a particle filter. We further develop a number of informed reversible transformations to sample the model probability space in order to maximize our model posterior probability. The novelty of our tracking approach also comes from a way we formulate observation likelihoods to account for 3D locations of the bodies with respect to the camera and occlusions by other tracked human bodies as well as static objects. The results of tracking on color and thermal sequences demonstrate that our algorithm is robust to illumination noise and performs well in the outdoor environments. © 2006 ieee.

关键词： Object recognition

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A sequential vehicle classifier for infrared video using multinomial pattern matching

A sequential vehicle classifier for infrared video using mul...

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2006 conference on computer vision and pattern recognition workshops

作者： Koch, Mark W. Malone, Kevin T. Dept. of Sensor Exploitation Applications Sandia National Laboratories Albuquerque NM 87185 United States Dept. of Signal Processing Applications Sandia National Laboratories Albuquerque NM 87185 United States

ISBN: (纸本)0769526462

Vehicle classification is a challenging problem, since vehicles can take on many different appearances and sizes due to their form and function, and the viewing conditions. The low resolution of uncooled-infrared video and the large variability of naturally occurring environmental conditions can make this an even more difficult problem. We develop a multilook fusion approach for improving the performance of a single look system. Our single look approach is based on extracting a signature consisting of a histogram of gradient orientations from a set of regions covering the moving object. We use the multinomial pattern matching algorithm to match the signature to a database of learned signatures. To combine the match scores of multiple signatures from a single tracked object, we use the sequential probability ratio test. Using real infrared data we show excellent classification performance, with low expected error rates, when using at least 25 looks. © 2006 ieee.

关键词： pattern matching

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Keystroke biometric recognition studies on long-text input under ideal and application-oriented conditions

Keystroke biometric recognition studies on long-text input u...

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2006 conference on computer vision and pattern recognition workshops

作者： Villani, Mary Tappert, Charles Ngo, Giang Simone, Justin St. Fort, Huguens Cha, Sung-Hyuk School of CSIS Pace University Pleasantville NY 10570

ISBN: (纸本)0769526462

A long-text-input keystroke biometric system was developed for applications such as identifying perpetrators of inappropriate e-mail or fraudulent Internet activity. A Java applet collected raw keystroke data over the Internet, appropriate long-text-input features were extracted, and a pattern classifier made identification decisions. Experiments were conducted on a total of 118 subjects using two input modes - copy and free-text input - and two keyboard types -desktop and laptop keyboards. Results indicate that the keystroke biometric can accurately identify an individual who sends inappropriate email (free text) if sufficient enrollment samples are available and if the same type of keyboard is used to produce the enrollment and questioned samples. For laptop keyboards we obtained 99.5% accuracy on 36 users, which decreased to 97.9% on a larger population of 47 users. For desktop keyboards we obtained 98.3% accuracy on 36 users, which decreased to 93.3% on a larger population of 93 users. Accuracy decreases significantly when subjects used different keyboard types or different input modes for enrollment and testing. © 2006 ieee.

关键词： pattern recognition

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Liveness detection for fingerprint scanners based on the statistics of wavelet signal processing

Liveness detection for fingerprint scanners based on the sta...

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2006 conference on computer vision and pattern recognition workshops

作者： Tan, Bozhao Schuckers, Stephanie Department of Electrical and Computer Engineering Clarkson University Potsdam NY 13699 United States

ISBN: (纸本)0769526462

Fingerprint scanners can be spoofed by artificial fingers using moldable plastic, clay, Play-Doh, gelatin, silicone rubber materials, etc. Liveness detection is an anti-spoofing method which can detect physiological signs of life from fingerprints to ensure only live fingers can be captured for enrollment or authentication. In this paper, a new method based on the wavelet transform on the ridge signal extracted along the ridge mask is proposed which can detect the perspiration phenomenon using only a single image. Statistical features are extracted for multiresolution scales to discriminate between live and non-live fingers. Based on these features, we use a classification tree to generate the decision rules for the liveness classification. We test this method on the dataset which contains about 58 live, 80 spoof (50 made from Play-Doh and 30 made from gelatin), and 25 cadaver subjects for 3 different scanners. Also, we test this method on a second dataset which contains 33 live and 33 spoof (made from gelatin) subjects. The proposed liveness detection method is purely software based and application of this method can provide anti-spoofing protection for fingerprint scanners. © 2006 ieee.

关键词： pattern recognition systems

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Efficient Maximally Stable Extremal Region (MSER) tracking

Efficient Maximally Stable Extremal Region (MSER) tracking

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Donoser, Michael Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology

ISBN: (纸本)0769525970

This paper introduces a tracking method for the well known local MSER (Maximally Stable Extremal Region) detector. The component tree is used as an efficient data structure, which allows the calculation of MSERs in quasi-linear time. It is demonstrated that the tree is able to manage the required data for tracking. We show that by means of MSER tracking the computational time for the detection of single MSERs can be improved by a factor of 4 to 10. Using a weighted feature vector for data association improves the tracking stability. Furthermore, the component tree enables backward tracking which further improves the robustness. The novel MSER tracking algorithm is evaluated on a variety of scenes. In addition, we demonstrate three different applications, tracking of license plates, faces and fibers in paper, showing in all three scenarios improved speed and stability. © 2006 ieee.

关键词： pattern recognition

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Optimal pose for face recognition

Optimal pose for face recognition

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Liu, Xiaoming Chen, Tsuhan Rittscher, Jens Visualization and Computer Vision Lab. General Electric Global Research Center Schenectady NY 12309 Advanced Multimedia Processing Lab. Carnegie Mellon University Pittsburgh PA 15213

ISBN: (纸本)0769525970

Researchers in psychology have well studied the impact of the pose of a face as perceived by humans, and concluded that the so-called 3/4 view, halfway between the front view and the profile view, is the easiest for face recognition by humans. For face recognition by machines, while much work has been done to create recognition algorithms that are robust to pose variation, little has been done in finding the most representative pose for recognition. In this paper, we use a number of algorithms to evaluate face recognition performance when various poses are used for training. The result, similar to findings in psychology that the 3/4 view is the best, is also justified by the discrimination power of different regions on the face, computed from both the appearance and the geometry of these regions. We believe our study is both scientifically interesting and practically beneficial for many applications. © 2006 ieee.

关键词： Face recognition

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Classifying human dynamics without contact forces

Classifying human dynamics without contact forces

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Bissacco, Alessandro Soatto, Stefano Computer Science Department University of California Los Angeles Los Angeles CA 90095

ISBN: (纸本)0769525970

We develop a classification algorithm for hybrid autoregressive models of human motion for the purpose of video-based analysis and recognition. We assume that some temporal statistics are extracted from the images, and we use them to infer a dynamical system that explicitly models contact forces. We then develop a distance between such models that explicitly factors out exogenous inputs that are not unique to an individual or her gait. We show that such a distance is more discriminative than the distance between simple linear systems, where most of the energy is devoted to modeling the dynamics of spurious nuisances such as contact forces. © 2006 ieee.

关键词： Classification (of information)

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Using bilinear models for view-invariant action and identity recognition

Using bilinear models for view-invariant action and identity...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Cuzzolin, Fabio UCLA Vision Lab. University of California at Los Angeles Boelter Hall 90025 Los Angeles CA

ISBN: (纸本)0769525970

Human identification from gait is a challenging task in realistic surveillance scenarios in which people walking along arbitrary directions are imaged by a single camera. In this paper, motivated by the view-invariance issue in the human ID from gait problem, we address the general problem of classifying the "content" of human motions of unknown "style". Given a dataset of sequences in which different people walking normally are seen from several well-separated views, we propose a three-layer scheme based on bilinear models, in which image sequences are mapped to observation vectors of fixed dimension using Markov modeling. We test our approach on the CMU Mobo database, showing how bilinear separation outperforms other approaches, opening the way to view- and action-invariant identity recognition, as well as subject- and view-invariant action recognition. © 2006 ieee.

关键词： Gesture recognition

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An efficiency criterion for 2D shape model selection

An efficiency criterion for 2D shape model selection

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Leonard, Kathryn Department of Applied and Computational Mathematics California Institute of Technology

ISBN: (纸本)0769525970

We propose efficiency of representation as a criterion for evaluating shape models, then apply this criterion to compare the boundary curve representation with the medial axis. We estimate the Ε-entropy of two compact classes of curves. We then construct two adaptive encodings for non-compact classes of shapes, one using the boundary curve and the other using the medial axis, and determine precise conditions for when the medial axis is more efficient. Along the way we construct explicit near-optimal boundary-based approximations for compact classes of shapes and an explicit compression scheme for non-compact classes of shapes based on the medial axis. We end with an application of the criterion to shape data. © 2006 ieee.

关键词： pattern recognition

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