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3D Periodic Human Motion Reconstruction from 2D Motion Sequences

3D Periodic Human Motion Reconstruction from 2D Motion Seque...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Zonghua Zhang N.F. Troje BioMotionLab Department of Psychology Queen's University Belfast Canada

In this report, we present and evaluate a method of reconstructing three-dimensional (3D) periodic human motion from two-dimensional (2D) motion sequences. Based on a Fourier decomposition of a training set of 3D data, we construct a linear, morphable representation. Using this representation a low-dimensional linear model is learned by means of Principle Component Analysis (PCA). Two-dimensional test data are now projected onto this model and the resulting 3D reconstructions are evaluated. We present two different simulations. In the first experiment, we assume the 2D projection matrix to be known. In the second experiment, the horizontal viewpoint is unknown and is being recovered from the data.

关键词： Humans Image reconstruction Motion analysis Biological system modeling Surveillance Visual system pattern recognition computer vision Image recognition Shape

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Information Scaling Laws in Natural Scenes

Information Scaling Laws in Natural Scenes

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Cheng-En Guo Ying Nian Wu Song Chun Zhu Departments of Computer Science University of California Los Angeles USA Departments of Statistics University of California Los Angeles USA

In natural scenes, objects and patterns can appear at a wide variety of distances from the viewer. For the same visual pattern viewed at different distances, both the image and our perception of the pattern change over distance. We call the change of the image over distance as image scaling, and the change of our perception over distance as information scaling. While image scaling can be accounted for by the state space theory, information scaling has not been mathematically studied in computer vision. In this paper, we prove two information scaling laws: 1) the entropy rate of the image changes over distance, and 2) the entropy of the posterior distribution of the pattern also changes over distance. These two information scaling laws have deep implications in computer vision: they call for different models of the same visual pattern at different distances, as well as a model transition mechanism for switching models over different distance/scale regimes.

关键词： Layout Entropy computer vision Image coding computer science Statistics State-space methods Face recognition Eyes Nose

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Ontology-Driven Bayesian Networks for Dynamic Scene Understanding

Ontology-Driven Bayesian Networks for Dynamic Scene Understa...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： C. Town Computer Laboratory University of Cambridge Cambridge UK

This paper describes how an ontology consisting of a ground truth schema and a set of annotated training sequences can be used to train the structure and parameters of Bayesian networks for event recognition. It is shown how the performance of such networks can be improved by augmenting the original ontology with visual object detection, appearance modelling and tracking methods. The integration of these different sources of evidence is optimised with reference to the syntactic and semantic constraints of the ontology. Through the application of these techniques to a visual surveillance problem, it is shown how high-level event, object and scenario properties may be inferred on the basis of the visual content descriptors and an ontology of states, roles, situations and scenarios which is derived from a pre-defined ground truth schema. Performance analysis of the resulting framework allows alternative ontologies to be compared for their self-consistency and realisability in terms of the different visual detection and tracking modules.

关键词： Ontologies Bayesian methods Layout Surveillance Performance analysis computer vision Object detection Data mining Cities and towns computer networks

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Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures

Real-Time Inference of Complex Mental States from Facial Exp...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： R. El Kaliouby P. Robinson Computer Laboratory University of Cambridge Cambridge UK

This paper presents a system for inferring complex mental states from video of facial expressions and head gestures in real-time. The system is based on a multi-level dynamic Bayesian network classifier which models complex mental states as a number of interacting facial and head displays, identified from component-based facial features. Experimental results for 6 mental states groups- agreement, concentrating, disagreement, interested, thinking and unsure are reported. Real-time performance, unobtrusiveness and lack of preprocessing make our system particularly suitable for user-independent human computer interaction.

关键词： Real time systems computer displays Bayesian methods Facial features Face Feature extraction Laboratories Human computer interaction User interfaces Emotion recognition

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Learning Perceptual Organization with a Developmental Robot

Learning Perceptual Organization with a Developmental Robot

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： R. Driancourt Intelligent Robot Laboratory University of Tsukuba Japan

This paper presents a biologically-inspired model of self-organization for robotic intermediary vision. Two mechanisms are under concern. First, the development of low-level local feature detectors adapted to the sensory input signal statistics in order to perform a piecewise categorization of the sensory signal. Second, the hierarchical grouping of these local features in a holistic perception. While the grouping mechanism is expressed as a classical agglomerative clustering, underlying similarity measures are not pre-given but developed from the signal statistics. Segmentation results are therefore adapted to the robot's experience. Based on information-theory, a stopping criterion that expresses a "good" abstraction level is proposed. Proposed mechanisms are illustrated with examples in both color and edge segmentation.

关键词： Robot sensing systems computer vision Statistics Cognitive robotics Biological system modeling Detectors Robotics and automation Focusing Neural networks Intelligent robots

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Manifold Based Analysis of Facial Expression

Manifold Based Analysis of Facial Expression

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Changbo Hu Ya Chang R. Feris M. Turk University of California Santa Barbara USA

We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embedding. In this space, facial contour features are first clustered, using a mixture model. Then, expression dynamics are learned for tracking and classification. We use ICondensation to track facial features in the embedded space, while recognizing facial expressions in a cooperative manner, within a common probabilistic framework. The image observation likelihood is derived from a variation of the Active Shape Model (ASM) algorithm. For each cluster in the low-dimensional space, a specific ASM model is learned, thus avoiding incorrect matching due to non-linear image variations. Preliminary experimental results show that our probabilistic facial expression model on manifold significantly improves facial deformation tracking and expression recognition.

关键词： Face recognition Deformable models Active shape model computer vision Video sequences Active appearance model pattern recognition Particle tracking Facial features Clustering algorithms

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Real-Time Stereo by using Dynamic Programming

Real-Time Stereo by using Dynamic Programming

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： S. Forstmann Y. Kanou Jun Ohya S. Thuering A. Schmitt 3D Inc. Yokohama Japan Waseda University Tokyo Japan Karlsruhe University Karlsruhe Germany

A Dynamic Programming (DP) based algorithm that achieves real-time, high quality stereo-matching is presented. A special coarse to fine approach as well as the MMX based assembler implementation mainly contribute to the reached computation speed. A novel vertical smoothing approach by re-integrating paths inside the DP matching allows the avoidance of noisy horizontal strokes, so that high quality stereo-matching is achieved. The current implementation capable of running at about 30 FPS on an 2.2GHz PC, which is sufficient for the utilization in real-time applications.

关键词： Dynamic programming Smoothing methods Application software History Assembly Machine vision Image reconstruction Hardware Computational complexity Stereo vision

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A Statistical Approach to Large Deformation Diffeomorphisms

A Statistical Approach to Large Deformation Diffeomorphisms

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： B. Markussen Department of Computer Science University of Copenhagen Copenhagen Denmark

This paper is concerned with the theory of non-rigid registration and image warping. Our approach combines the Brownian warps model proposed by Nielsen et al. with the differential operator approach proposed by Joshi & Miller. Using standard statistical assumptions we derive a stochastic differential equation generating flows of diffeomorphisms of d-dimensional space. The coefficients in the stochastic differential equation encode the statistical properties of the flow and the driving Brownian motions encode the actual appearance of the flow. We discuss the choice of the coefficients and introduce a renormalization for the Brownian motions. The renormalization allows for maximum a posteriori estimation of the unobserved Brownian motions. Finally we investigate the landmark matching problem.

关键词： Differential equations Stochastic processes Rubber computer science Maximum a posteriori estimation Law Legal factors Topology Paints Spline

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A Tool for Range Sensing and Environment Discovery for the Blind

A Tool for Range Sensing and Environment Discovery for the B...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： D. Yuan R. Manduchi Department of Computer Engineering University of California Santa Cruz USA

This paper describes the development of a hand-held environment discovery tool for the blind. The final device will be composed of a laser-based range sensor and of an onboard processor. As the user swings the hand-held system around, he/she will receive local range information by means of a tactile interface. In addition, the time profile of the range will be analyzed by the onboard processor to detect environmental features that are critical for mobility, such as curbs, steps and drop-offs. In our current implementation, range is collected by a short-baseline triangulation system formed by a point laser and a miniaturized camera, producing readings at frame rate. An Extended Kalman filter is used to track the range data and detect environmental features of interest.

关键词： Time of arrival estimation Environmental economics computer vision Ultrasonic imaging Wheelchairs Layout Handheld computers Cameras Blindness Area measurement

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Maximum Response Filters for Texture Analysis

Maximum Response Filters for Texture Analysis

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： G. Caenen L. Van Gool ESAT-PSI-VISICS University of Leuven Belgium Computer Vision Group (BIWI) ETH Zurich Switzerland

Current texture analysis focuses either on gathering correlations between image patches and filters, or on explicitly modeling the dependencies between pixels. Both strategies are unable to cope directly with changes in scale, or more general, in viewpoint and illumination. To accommodate to these extra variations, texture segmentation analyzes the texture over multiple scales and classification algorithms include multiple models for a single texture class. We propose a filter-based texture model that allows for a more compact texture representation, independent of viewpoint and illumination. This is achieved by locally optimizing the filter responses through a predefined set of transformations of the filter support. Results are shown for both texture classification and texture segmentation experiments.

关键词： Image texture analysis Gabor filters Image segmentation computer vision Image analysis Pixel Lighting Markov random fields Statistics Convolution

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