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Tracking With Sobolev Active Contours

Tracking With Sobolev Active Contours

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Sundaramoorthi J.D. Jackson A. Yezzi A.C. Mennucci School of Electrical and Computer Engineering Georgia Institute of Technology USA Scuola Normale Superiore Italy

Recently proposed Sobolev active contours introduced a new paradigm for minimizing energies defined on curves by changing the traditional cost of perturbing a curve and thereby redefining their gradients. Sobolev active contours evolve more globally and are less attracted to certain intermediate local minima than traditional active contours. In this paper we analyze Sobolev active contours in the Fourier domain in order to understand their evolution across different scales. This analysis shows an important and useful behavior of Sobolev contours, namely, that they move successively from coarse to increasingly finer scale motions in a continuous manner. Along with other properties, the previous observation reveals that Sobolev active contours are ideally suited for tracking problems that use active contours. Our purpose in this work is to show how a variety of active contour based tracking methods can be significantly improved merely by evolving the active contours according to the Sobolev method.

关键词： Active contours Shape Costs Motion analysis Video sequences Image edge detection Robustness Deformable models

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Active object recognition

Active object recognition

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Wilkes J.K. Tsotsos Department of Computer Science University of Toronto Toronto Canada

The concept of active object recognition is introduced, and a proposal for its solution is described. The camera is mounted on the end of a robot arm on a mobile base. The system exploits the mobility of the camera by using low-level image data to drive the camera to a standard viewpoint with respect to an unknown object. From such a viewpoint, the object recognition task is reduced to a two-dimensional pattern recognition problem. The system uses an efficient tree-based, probabilistic indexing scheme to find the model object that is likely to have generated the observed data, and for line tracking uses a modification of the token-based tracking scheme of J.L. Crowley et al. (1988). The system has been successfully tested on a set of origami objects. Given sufficiently accurate low-level data, recognition time is expected to grow only logarithmically with the number of objects stored.< >

关键词： Object recognition Cameras Robot vision systems Light sources Image recognition Geometry computer science Proposals Mobile robots pattern recognition

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Competitive mixture of deformable models for pattern classification

Competitive mixture of deformable models for pattern classif...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Kwok-Wai Cheung Dit-Yan Yeung R.T. Chin Department of Computler Science Hong Kong University of Science and Technology Hong Kong China Hong Kong University of Science and Technology Kowloon HK Dept. of Comput. Sci. Hong Kong Univ. of Sci. & Technol. Clear Water Bay Hong Kong

Following the success of applying deformable models to feature extraction, a natural next step is to apply such models to pattern classification. Recently, we have cast a deformable model under a Bayesian framework for classification, giving promising results. However, deformable model methods are computationally expensive due to the required iterative optimization process. The problem is even more severe when there are a large number of models (e.g., for character recognition), because each of them has to deform and match with the input data before a final classification can be derived. In this paper, we propose to combine the deformable models into a mixture, in which the individual models compete with each other to survive the matching process during classification. Models that do not compete well are eliminated early, thus allowing substantial savings in computation. This process of competition-elimination has been applied to handwritten digit recognition in which significant speedup can be achieved without sacrificing recognition accuracy.

关键词： Deformable models pattern classification Bayesian methods Handwriting recognition Feature extraction Image recognition Delta modulation pattern recognition Context modeling Iterative methods

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Editable dynamic textures

Editable dynamic textures

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Doretto S. Soatto Computer Science Department UCLA Los Angeles CA USA

We present a simple and efficient algorithm for modifying the temporal behavior of "dynamic textures," i.e. sequences of images that exhibit some form of temporal regularity, such as flowing water, steam, smoke, flames, foliage of trees in wind. The main goal is to design algorithms for synthesizing and editing realistic sequences of images of dynamic scenes that exhibit some form of temporal stationarity. This is an image-based rendering task, and in particular we are interested in synthesizing the temporal behavior of the scene.

关键词： Layout Fires Rendering (computer graphics) Bioreactors Solid modeling Legged locomotion Signal generators Geometry Photometry Visualization

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Scalable discriminant feature selection for image retrieval and recognition

Scalable discriminant feature selection for image retrieval ...

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conference on computer vision and pattern recognition (cvpr)

作者： N. Vasconcelos M. Vasconcelos Statistical Visual Computing Laboratory University of California San Diego USA Harvard Robotics Laboratory Harvard University USA

Problems such as object recognition or image retrieval require feature selection (FS) algorithms that scale well enough to be applicable to databases containing large numbers of image classes and large amounts of data per class. We exploit recent connections between information theoretic feature selection and minimum Bayes error solutions to derive FS algorithms that are optimal in a discriminant sense without compromising scalability. We start by formalizing the intuition that optimal FS must favor discriminant features while penalizing discriminant features that are redundant. We then rely on this result to derive a new family of FS algorithms that enables an explicit trade-off between complexity and classification optimality. This trade-off is controlled by a parameter that encodes the order of feature redundancies that must be explicitly modeled to achieve the optimal solution. Experimental results on databases of natural images show that this order is usually low, enabling optimal FS with very low complexity.

关键词： Image retrieval Image recognition Scalability Laboratories Information retrieval Image databases Spatial databases Face detection Large-scale systems Biology computing

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The integration of optical flow and deformable models with applications to human face shape and motion estimation

The integration of optical flow and deformable models with a...

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conference on computer vision and pattern recognition (cvpr)

作者： D. DeCarlo D. Metaxas Department of Computer & Infiormation Science University of Pennsylvania Philadelphia PA USA

We present a formal methodology for the integration of optical flow and deformable models. The optical flow constraint equation provides a non-holonomic constraint on the motion of the deformable model. In this augmented system, forces computed from edges and optical flow are used simultaneously. When this dynamic system is solved, a model-based least-squares solution for the optical flow is obtained and improved estimation results are achieved. The use of a 3-D model reduces or eliminates problems associated with optical flow computation. This approach instantiates a general methodology for treating visual cues as constraints on deformable models. We apply this framework to human face shape and motion estimation. Our 3-D deformable face model uses a small number of parameters to describe a rich variety of face shapes and facial expressions. We present experiments in extracting the shape and motion of a face from image sequences.

关键词： Integrated optics Image motion analysis Deformable models Optical computing Shape Equations Humans Face Motion estimation Image sequences

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Optimal servoing for active foveated vision

Optimal servoing for active foveated vision

引用

conference on computer vision and pattern recognition (cvpr)

作者： H.P. Rotstein E. Rivlin Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel Department of Computer Science Technion-Israel Institute of Technology Haifa Israel

Foveated vision and two-mode tracking, as inspired by the human oculomotor system, are often used in active vision system. The purpose of this paper is to provide answers to the following basic questions which arise from implementations. First, is it beneficial to have foveated vision and what is the optimal size of the foveal window? Second, is there a need for two control mechanisms (smooth pursuit and saccade) for improved performance and how can one efficiently switch between them? In order to do so, a setup is proposed in which these strategies can be evaluated in a systematic manner. It is shown that the fovea appears as a compromise between the tightness of the tracking specifications and computational constraints. Introducing a model for the later and postulating some a priori knowledge of the target behavior, it is possible to compute the size of the fovea in an optimal way. As a by-product, "smooth-pursuit" can be defined in a natural way, and the use of a two-mode tracking scheme is justified. The second mode, i.e. "saccadic control", aims at re-centering the target on the fovea so that the smooth pursuit controller can continue to operate. It is shown that a control strategy can indeed be defined so that this objective can be met under appropriate operating conditions.

关键词： Target tracking Control systems Humans Machine vision Magnetic heads Switches Robot vision systems Cameras Visual system Motion control

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Modelling solids of revolution by monocular vision

Modelling solids of revolution by monocular vision

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conference on computer vision and pattern recognition (cvpr)

作者： J.M. Lavest R. Glachet M. Dhome J.T. Lapreste Electronics Laboratory URA 830 of the CNRS Blaise Pascal University Clermont-Ferrand II Aubiere France

A system is presented for modelling solids of revolution from a set of a few monocular images. The reconstruction is obtained by assuming only that the viewed object belongs to this particular class of objects. The knowledge of the camera displacement between each image is not required. The modeling is based on the resolution of the inverse perspective problem for the contour points detected in the different images.< >

关键词： Solid modeling Image reconstruction Position measurement Cameras Laboratories Image resolution Object detection

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Particle filter with state permutations for solving image jigsaw puzzles

Particle filter with state permutations for solving image ji...

引用

作者： Yang, Xingwei Adluru, Nagesh Latecki, Longin Jan Department of Computer and Information Sciences Temple University Philadelphia United States Department of Biostatistics and Medical Informatics University of Winsconsin Madison United States

ISBN: (纸本)9781457703942

We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instance of this problem is NP-complete, and it is also challenging for humans, since in the considered setting the original image is not given. Recently a graphical model has been proposed to solve this and related problems. The target label probability function is then maximized using loopy belief propagation. We also formulate the problem as maximizing a label probability function and use exactly the same pairwise potentials. Our main contribution is a novel inference approach in the sampling framework of Particle Filter (PF). Usually in the PF framework it is assumed that the observations arrive sequentially, e.g., the observations are naturally ordered by their time stamps in the tracking scenario. Based on this assumption, the posterior density over the corresponding hidden states is estimated. In the jigsaw puzzle problem all observations (puzzle pieces) are given at once without any particular order. Therefore, we relax the assumption of having ordered observations and extend the PF framework to estimate the posterior density by exploring different orders of observations and selecting the most informative permutations of observations. This significantly broadens the scope of applications of the PF inference. Our experimental results demonstrate that the proposed inference framework significantly outperforms the loopy belief propagation in solving the image jigsaw puzzle problem. In particular, the extended PF inference triples the accuracy of the label assignment compared to that using loopy belief propagation. © 2011 ieee.

关键词： Bandpass filters

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Shape Guided Object Segmentation

Shape Guided Object Segmentation

引用

conference on computer vision and pattern recognition (cvpr)

作者： E. Borenstein J. Malik Division of Applied Mathematics Brown University USA Department of Electrical Engineering and Computer Science University of California Berkeley USA

We construct a Bayesian model that integrates topdown with bottom-up criteria, capitalizing on their relative merits to obtain figure-ground segmentation that is shape-specific and texture invariant. A hierarchy of bottom-up segments in multiple scales is used to construct a prior on all possible figure-ground segmentations of the image. This prior is used by our top-down part to query and detect object parts in the image using stored shape templates. The detected parts are integrated to produce a global approximation for the object’s shape, which is then used by an inference algorithm to produce the final segmentation. Experiments with a large sample of horse and runner images demonstrate strong figure-ground segmentation despite high object and background variability. The segmentations are robust to changes in appearance since the matching component depends on shape criteria alone. The model may be useful for additional visual tasks requiring labeling, such as the segmentation of multiple scene objects.

关键词： Shape Object segmentation Image segmentation Bayesian methods Object detection Approximation algorithms Inference algorithms Horses Robustness Labeling

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