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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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Using associative memory principles to enhance perceptual ability of vision systems

Using associative memory principles to enhance perceptual ab...

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Gorodnichy, Dmitry O. Gorodnichy, Oleg P. Institute for Information Technology National Research Council of Canada Montreal Rd M-50 OttawaK1A 0R6 Canada Kiev State University of Information and Communication Technologies Solomenskaya Str 7 Kiev03110 Ukraine

The so called associative thinking, which humans are known to perform on every day basis, is attributed to the fact that human brain memorizes information using the dynamical system made of interconnected neurons. Retrieval of information in such a system is accomplished in associative sense;starting from an arbitrary state, which might be an encoded representation of a visual image, the brain activity converges to another state, which is stable and which is what the brain remembers. In this paper we explore the possibility of using an associative memory for the purpose of enhancing the interactive capability of perceptual vision systems. By following the biological memory principles, we show how vision systems can be designed to recognize faces, facial gestures and orientations, using low-end video-cameras and little computational power. In doing that we use the public domain associative memory code. © 2004 ieee.

关键词： Video cameras

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Differential structure in non-linear image embedding functions

Differential structure in non-linear image embedding functio...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Pless, Robert Department of Computer Science Washington University St. Louis United States

Many natural image sets are samples of a low dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of basis images, then linear dimensionality reduction techniques such as PCA and ICA fail, and non-linear dimensionality reduction techniques are required to automatically determine the intrinsic structure of the image set. Recent techniques such as ISOMAP and LLE provide a mapping between the images and a low dimensional parameterization of the images. In this paper we consider how choosing different image distance metrics affects the low-dimensional parameterization. For image sets that arise from non-rigid and human motion analysis, and MRI applications, differential motions in some directions of the low-dimensional space correspond to common transformations in the image domain. Defining distance measures that are invariant to these transformations makes Isomap a powerful tool for automatic registration of large image or video data sets. © 2004 ieee.

关键词： Magnetic resonance imaging

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Globally optimal segmentation of interacting surfaces with geometric constraints

Globally optimal segmentation of interacting surfaces with g...

引用

Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Li, Kang Wu, Xiaodong Chen, Danny Z. Sonka, Milan Department of Electrical Engineering University of Iowa Iowa City IA 52242-1595 Department of Computer Science University of Texas - Pan American Edinburg TX 78539 Dept. of Comp. Sci. and Engineering University of Notre Dame Notre Dame IN 46556

Efficient detection of globally optimal surfaces representing object boundaries in volumetric datasets is important and remains challenging in many medical image analysis applications. We have developed an optimal surface detection method that is capable of simultaneously detecting multiple interacting surfaces, in which the optimality is controlled by the cost functions designed for individual surfaces and several geometric constraints defining the surface smoothness and interrelations. The method solves the surface detection problems by transforming them into computing minimum s-t cuts in the derived edge-weighted directed graphs. The proposed algorithm has low-order polynomial complexity and is computationally efficient The method has been validated on over 100 computer generated volumetric images and 96 CT-scanned datasets of different-sized plexiglas tubes, yielding highly accurate results (mean signed error of the measured inner- and outer-diameters of the plexiglas tubes was 0.21 × 3.20%). Our approach can be readily extended to higher dimensional image segmentation.

关键词： computer vision

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A generalized temporal context model for semantic scene classification

A generalized temporal context model for semantic scene clas...

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Boutell, Matthew Luo, Jiebo Department of Computer Science University of Rochester United States Research and Development Laboratories Eastman Kodak Company United States

Semantic scene classification is an open problem in computer vision especially when information from only a single image is employed. In applications involving image collections, however, images are clustered sequentially, allowing surrounding images to be used as temporal context. We present a general probabilistic temporal context model in which the first-order Markov property is used to integrate content-based and temporal context cues. The model uses elapsed time-dependent transition probabilities between images to enforce the fact that images captured within a shorter period of time are more likely to be related. This model is generalized in that it allows arbitrary elapsed time between images, making it suitable for classifying image collections. We also derived a variant of this model to use in image collections for which no timestamp information is available, such as film scans. We applied the context models to two problems, achieving significant gains in accuracy in both cases. The two algorithms used to implement inference within the context model, Viterbi and belief propagation, yielded similar results. © 2004 ieee.

关键词： Belief propagation

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Names and faces in the news

Names and faces in the news

引用

Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Berg, Tamara L. Berg, Alexander C. Edwards, Jaety Maire, Michael White, Ryan Teh, Yee-Whye Learned-Miller, Erik Forsyth, D.A. Computer Science Division U.C. Berkeley Berkeley CA 94720

We show quite good face clustering is possible for a dataset of inaccurately and ambiguously labelled face images. Our dataset is 44,773 face images, obtained by applying a face finder to approximately half a million captioned news images. This dataset is more realistic than usual face recognition datasets, because it contains faces captured "in the wild" in a variety of configurations with respect to the camera, taking a variety of expressions, and under illumination of widely varying color. Each face image is associated with a set of names, automatically extracted from the associated caption. Many, but not all such sets contain the correct name. We cluster face images in appropriate discriminant coordinates. We use a clustering procedure to break ambiguities in labelling and identify incorrectly labelled faces. A merging procedure then identifies variants of names that refer to the same individual. The resulting representation can be used to label faces in news images or to organize news pictures by individuals present. An alternative view of our procedure is as a process that cleans up noisy supervised data. We demonstrate how to use entropy measures to evaluate such procedures.

关键词： Face recognition

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Graph partitioning active contours for knowledge-based geo-spatial segmentation

Graph partitioning active contours for knowledge-based geo-s...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Sumengen, Baris Bhagavathy, Sitaram Manjunath, B.S. Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States

Our contribution in this paper is two-fold. First, we extend our previous curve evolution method based on pairwise similarities. This curve evolution equation combines the grouping abilities of active contours and graph partitioning techniques. Connections of our method to spectral graph partitioning are investigated and comparisons are made. Second, in a model-based segmentation scenario, we propose a method to improve segmentation quality by iteratively modifying the model using feedback from segmentation of a labeled training set. Our purpose here is to segment objects in geo-spatial images by integrating domain knowledge with the segmentation method. We achieve our goal by combining a statistical model for the object with a knowledge-guided segmentation method. Experimental results show that this framework is effective for model-based segmentation of complex geo-spatial objects. © 2004 ieee.

关键词： Image segmentation

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Learning a factorized segmental representation of far-field tracking data

Learning a factorized segmental representation of far-field ...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Stauffer, Chris Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States

There are many useful observable characteristics of the state of a tracked object. These characteristics could include normalized size, normalized speed, normalized direction, object color, position, and object shape among other characteristics. Although these characteristics are by no means completely independent of each other, it is desirable to determine a separate, compact description of each of each of these aspects. Using this compact factored description, different aspects of individual sequences can be estimated and described without overwhelming computational or storage costs. In this work, we describe Factored Latent Analysis (FLA) and its application to deriving factored models for segmenting sequences in each of K separate characteristics. This method exploits temporally local statistics within each of the latent aspects and their inter-dependencies to derive a model that allows segmentation of each of the observed characteristics. This method is data driven and unsupervised. Activity classification results for multiple challenging environments are shown. © 2004 ieee.

关键词： Digital storage

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Nonlinear generative models for dynamic shape and dynamic appearance

Nonlinear generative models for dynamic shape and dynamic ap...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Elgammal, Ahmed Department of Computer Science Rutgers University PiscatawayNJ United States

Our objective is to learn representations for the shape and the appearance of moving (dynamic) objects that supports tasks such as synthesis, pose recovery, reconstruction and tracking. In this paper we introduce a framework that aim to learn a landmark-free correspondence-free global representations of dynamic appearance manifolds. We use nonlinear dimensionality reduction to achieve an embedding of the global deformation manifold that preserves the geometric structure of the manifold. Given such embedding, a nonlinear mapping is learned from the embedding space into the visual input space. Therefore, any visual input is represented by a linear combination of nonlinear bases functions centered along the manifold in the embedding space. We also show how approximate solution for the inverse mapping can be obtained in a closed form which facilitate recovery of the intrinsic body configuration. We use the framework to learn the gait manifold as an example of a dynamic shape manifold, as well as to learn the manifolds for some simple gestures and facial expressions as examples of dynamic appearance manifolds. © 2004 ieee.

关键词： Mapping

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Learning chance probability functions for shape retrieval or classification

Learning chance probability functions for shape retrieval or...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Super, Boaz J. Computer Science Department University of Illinois at Chicago United States

Several example-based systems for shape retrieval and shape classification directly match input shapes to stored shapes, without using class membership information to perform the matching. We propose a method for improving the accuracy of this type of system. First, the system learns a set of chance probability functions (CPFs). The CPFs estimate the probabilities of obtaining a query shape with particular distances from each training example by chance. The learned CPFs are used at runtime to rapidly estimate the chance probabilities of the observed distances between the actual query shape and the database shapes. These estimated probabilities are then used as a dissimilarity measure for shape retrieval and/or nearest-neighbor classification. The CPF learning method is parameter-free. Experimental evaluation demonstrates that: (1) chance probabilities yield higher accuracy than Euclidean distances;(2) the learned CPFs support fast matching;and (3) the CPF-based system outperforms prior systems on a standard benchmark test of retrieval accuracy. © 2004 ieee.

关键词： Probability

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Simultaneous pose estimation and camera calibration from multiple views

Simultaneous pose estimation and camera calibration from mul...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Izo, Tomas Grimson, W. Eric L. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States

We present an algorithm to estimate the body pose of a walking person given synchronized video input from multiple uncalibrated cameras. We construct an appearance model of human walking motion by generating examples from the space of body poses and camera locations, and clustering them using expectation-maximization. Given a segmented input video sequence, we find the closest matching appearance cluster for each silhouette and use the sequence of matched clusters to extrapolate the position of the camera with respect to the person's direction of motion. For each frame, the matching cluster also provides an estimate of the walking phase. We combine these estimates from all views and find the most likely sequence of walking poses using a cyclical, feed-forward hidden Markov model. Our algorithm requires no manual initialization and no prior knowledge about the locations of the cameras. © 2004 ieee.

关键词： Hidden Markov models

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