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A topology preserving deformable model using level sets

A topology preserving deformable model using level sets

引用

conference on computer vision and pattern recognition (cvpr)

作者： Xiao Han Chenyang Xu J.L. Prince Center for Imaging Science Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA Siemens Corporate Research Inc. Princeton NJ USA

ISBN: (纸本)0769512720

Active contour and surface models, also known as deformable models, constitute a class of powerful segmentation techniques. Geometric deformable models implemented via level-set methods have advantages over parametric ones due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models, the ability to automatically handle topology changes, turns out to be a liability in applications where the objects to be segmented have a known topology that must be preserved. In this paper, we present a geometric deformable model that preserves topology using the simple point concept from digital topology. This algorithm maintains the other advantages of standard geometric deformable models including sub-pixel accuracy and production of nonintersecting curves (or surfaces). Several experiments on simulated and real data are provided to demonstrate the performance of the proposed algorithm.

关键词： Topology Deformable models Active contours Image segmentation Level set Lagrangian functions Brain Production Heart Image edge detection

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Robust change detection by fusing intensity and texture differences

Robust change detection by fusing intensity and texture diff...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Liyuan Li M.K.H. Leung KRDL RWCP Multi Modal Functions Laboratory Singapore Singapore School of Computer Engineering Nanyang technological University Singapore Singapore

ISBN: (纸本)0769512720

The paper proposes a novel technique for robust change detection based upon the integration of intensity and texture differences between two frames. A new texture difference measure based on the relations between gradient vectors is described. The robustness of the measure with respect to noise and illumination changes has been analyzed. Two ways to integrate the intensity and texture differences are proposed. The first combines two measures according to the weightage of texture evidence, while the second takes into additional constraint of smoothness. The parameters of the algorithm are selected automatically. The computational complexity analysis indicates that the proposed technique can run in real-time. Experimental results show that by exploiting both intensity and texture differences for change detection, one can obtain much better segmentation results than using the intensity or structure difference alone.

关键词： Lighting Noise robustness Image edge detection Motion detection Background noise Noise level Statistical distributions Noise measurement Change detection algorithms Computational complexity

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Optimal adaptive learning for image retrieval

Optimal adaptive learning for image retrieval

引用

conference on computer vision and pattern recognition (cvpr)

作者： Tao Wang Yong Rui Shi-Min Hu Department of Computer Science and Technology Tsinghua University Beijing China Microsoft Research Limited Redmond WA USA

ISBN: (纸本)0769512720

Learning-enhanced relevance feedback is one of the most promising and active research directions in content-based image retrieval. However, the existing approaches either require prior knowledge of the data or entail high computation costs, making them less practical. To overcome these difficulties and motivated by the successful history of optimal adaptive filters, we present a new approach to interactive image retrieval. Specifically, we cast the image retrieval problem in the optimal filtering framework, which does not require prior knowledge of the data, supports incremental learning, is simple to implement and achieves better performance than state-of-the-art approaches. To evaluate the effectiveness and robustness of the proposed approach, extensive experiments have been carried out on a large heterogeneous image collection with 17,000 images. We report promising results on a wide variety of queries.

关键词： Image retrieval Feedback Information retrieval Machine learning Learning systems Content based retrieval Computational efficiency Humans History Adaptive filters

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3D head tracking using motion adaptive texture-mapping

3D head tracking using motion adaptive texture-mapping

引用

conference on computer vision and pattern recognition (cvpr)

作者： L.M. Brown IBM Thomas J. Watson Research Center Hawthorne NY USA

ISBN: (纸本)0769512720

We have developed a fast robust 3D head tracking system based on rendering a texture-mapped cylinder. In order to handle the variable frame-to-frame motion changes, the system uses motion templates, which adapt to the current size of the motion increment. The relationship between measurable pixel energy and tracking error is used to design the parameters of the adaptive algorithm. To speedup processing and decouple rotational and translational motion, 2D positional information of the neckline is utilize. The confidence at each point is computed based on the amount of information used in creating the texture map and re-rendering the face. The system can also handle large out-of-plane rotations via additional templates. If the tracker fails, it can recover using an independent face detection routine. We compare the results of our approach with the extensive results of a closely related technique.

关键词： Face recognition Head Humans Image databases Robustness Face detection Facial animation Testing Energy measurement Algorithm design and analysis

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Structure and motion from uncalibrated catadioptric views

Structure and motion from uncalibrated catadioptric views

引用

conference on computer vision and pattern recognition (cvpr)

作者： C. Geyer K. Daniilidis GRASP Laboratory University of Pennsylvania Philadelphia PA USA

ISBN: (纸本)0769512720

In this paper we present a new algorithm for structure from motion from point correspondences in images taken from uncalibrated catadioptric cameras with parabolic mirrors. We assume that the unknown intrinsic parameters are three: the combined focal length of the mirror and lens and the intersection of the optical axis with the image. We introduce a new representation for images of points and lines in catadioptric images which we call the circle space. This circle space includes imaginary circles, one of which is the image of the absolute conic. We formulate the epipolar constraint in this space and establish a new 4/spl times/4 catadioptric fundamental matrix. We show that the image of the absolute conic belongs to the kernel of this matrix. This enables us to prove that Euclidean reconstruction is feasible from two views with constant parameters and from three views with varying parameters. In both cases, it is one less than the number of views necessary with perspective cameras.

关键词： Cameras Mirrors Lenses Image reconstruction Layout Books Calibration Laboratories Kernel Rendering (computer graphics)

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A framework for multiple snakes

A framework for multiple snakes

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conference on computer vision and pattern recognition (cvpr)

作者： T. Srinark C. Kambhamettu Department of Computer and Information Sciences University of Delaware Newark DE USA

ISBN: (纸本)0769512720

A framework for segmenting multiple objects in an image based on deformable contours is proposed. In this framework, multiple snakes are applied with a new kind of energy called the "group energy." The group energy is introduced to handle sharing of properties across multiple objects in the image. Our framework allows contours of "strong objects" to guide contours of "weak objects" by utilizing deformable templates. We also automatically generate the necessary weighting parameters for energy minimization. A new approach for multiple snake optimization which is based on dynamic programming is also proposed. We applied our framework to the problem of image analysis of gene expression in microarrays. Comprehensive experiments were performed and comparisons were made between the individual energy based method and the proposed group energy based method. Our results are highly encouraging and have many potential applications in a variety of tracking scenarios.

关键词： Active contours Image quality Image segmentation Data mining Object detection Deformable models Image edge detection Dynamic programming Image sequence analysis Contracts

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Learning probabilistic distribution model for multi-view face detection

Learning probabilistic distribution model for multi-view fac...

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conference on computer vision and pattern recognition (cvpr)

作者： Lie Gu S.Z. Li Hong-Jiang Zhang Microsoji Research China Beijing China

ISBN: (纸本)0769512720

Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose invariant face detection through. multi-view face distribution modeling. The approach is aimed to learn a set of low-dimensional subspaces from an originally nonlinear distribution by using the mixtures of probabilistic PCA. From the experiments, we found the learned PPCA models are of low dimensionality and exhibit high local linearity, and consequently offer an efficient representation for visual recognition. The model is then used to extract features and select "representative" negative training samples. Multi-view face detection is performed in the derived feature space by classifying each face into one of the view classes or into the nonface class, by using a multi-class SVM array classifier. The classification results from each view are fused together and yields the final classification results. The experimental results demonstrate the performance superiority of our proposed framework while performing multi-view face detection.

关键词： Face detection Principal component analysis Algorithm design and analysis Face recognition Linearity Feature extraction Support vector machines Support vector machine classification Layout Lighting

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Image magnification using level-set reconstruction

Image magnification using level-set reconstruction

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conference on computer vision and pattern recognition (cvpr)

作者： B.S. Morse D. Schwartzwald Department of Computer Science Brigham Young University Provo UT USA

ISBN: (纸本)0769512720

Image magnification is a common problem in imaging applications, requiring interpolation to "read between the pixels". Although many magnification/interpolation algorithms have been proposed in the literature, all methods must suffer to some degree the effects of imperfect reconstruction: false high-frequency content introduced by the underlying original sampling. Most often, these effects manifest themselves as jagged contours in the image. The paper presents a method for constrained smoothing of such artifacts that attempts to produce smooth reconstructions of the image's level curves while still maintaining image fidelity. This is similar to other iterative reconstruction algorithms and to Bayesian restoration techniques, but instead of assuming a smoothness prior for the underlying intensity function it assumes smoothness of the level curves. Results show that this technique can produce images whose error properties are equivalent to the initial approximation (interpolation) used, while their contour smoothness is both visually and quantitatively improved.

关键词： Image reconstruction Interpolation Surface fitting Image resolution Pixel Image sampling Printers Filtering Surface reconstruction Surface treatment

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Efficient spatiotemporal grouping using the Nystrom method

Efficient spatiotemporal grouping using the Nystrom method

引用

conference on computer vision and pattern recognition (cvpr)

作者： C. Fowlkes S. Belongie J. Malik University of California Berkeley CA USA University of California La Jolla CA USA

ISBN: (纸本)0769512720

Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation, but due to the computational demands, applications of such methods to spatiotemporal data have been slow to appear For even a short video sequence, the set of all pairwise voxel similarities is a huge quantity of data: one second of a 256/spl times/384 sequence captured at 30 Hz entails on the order of 10/sup 13/ pairwise similarities. The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning, making it feasible to apply them to very large spatiotemporal grouping problems. Our approach is based on a technique for the numerical solution of eigenfunction problems known as the Nystrom method This method allows extrapolation of the complete grouping solution using only a small number of "typical" samples. In doing so, we successfully exploit the fact that there are far fewer coherent groups in an image sequence than pixels.

关键词： Spatiotemporal phenomena Image sequences Image segmentation Eigenvalues and eigenfunctions computer applications Video sequences Extrapolation Pixel Educational institutions Psychology

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A hierarchical scheme for representing curves without self-intersections

A hierarchical scheme for representing curves without self-i...

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conference on computer vision and pattern recognition (cvpr)

作者： Pong-Sik Ho Min-Hwan Kim Department of Visual Technologies Dongeui Institute of Technology busan South Korea Department of Computer Engineering Pusan National University busan South Korea

ISBN: (纸本)0769512720

A hierarchical representation scheme for planar curves is proposed, which provides natural approximation and efficient localization. The scheme uses the iterative end-point fit algorithm (or Douglas-Peucker algorithm (D.H. Douglas and T.K. Peucker, 1973)), but approximation errors are adjusted by force to eliminate unnatural approximations. The error adjustment just makes the approximation error of a node in a hierarchical tree less than or equal to those of its ancestor. A self-intersection resolving algorithm is also developed to remove self-intersections in all the possible approximations for a curve, which uses the cross-link technique to reduce computation time remarkably. In point of localization, the bounding area of a curve is represented as a minimum bounding octangle (MBO), which can enclose the curve compactly. The MBO satisfies the hierarchical inclusion property which is useful for hierarchical geometrical operations, such as the polygon intersection test and the point-inclusion test. Through several experiments, we found that the proposed scheme always generated curve approximations without self-intersections and provided more natural representations than other hierarchical representation schemes such as the strip tree, the arc tree, and the HAL tree.

关键词： Shape Testing Strips Approximation error Approximation algorithms Iterative algorithms Application software computer vision Object recognition Animation

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