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2005 ieee computer Society Conference on computer vision and Pattern Recognition, CVPR 2005

作者： Solem, Jan Erik Kahl, Fredrik Heyden, Anders Applied Mathematics Group School of Technology and Society Malmö University Sweden Dept. of Computer Science and Engineering University of California San Diego San Diego CA United States

ISBN: (纸本)0769523722

The problem of feature-based surface reconstruction is considered in this paper. Our main contribution is the ability to handle visibility constraints, obtained from the projections of points, curves and silhouettes, in the surface fitting process. While traditional methods often ignore such information, we show that visibility constraints not only give better initial surface estimates and faster convergence, but also provide an important cue for determining surface topology. The problem is cast as a variational problem with constraints within the level set framework. It is shown how to evolve the surface without violating the visibility constraints using methods from variational calculus. Applications of the theory are detailed for a number of important cases of geometric primitives: points, curves and visual hulls. Several experiments on real image sequences are given to demonstrate the performance of the approach.

关键词： Image reconstruction

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Non-rigid shape comparison of implicitly-defined curves

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3rd International workshop on variational, Geometric, and level set methods in computer vision, VLSM 2005

作者： Thiruvenkadam, Sheshadri R. Graisser, David Chen, Yunmei University of California Los Angeles CA 90024 United States University of Florida Gainesville FL 32611 United States

ISBN: (纸本)3540293485

We present a novel variational model to find shape-based correspondences between two sets of level curves. While the usual correspondence techniques work with parametrized curves, we use a level-set formulation that enables us to handle curves with arbitrary topology. Given the functions Φ1 : (Ω1 ⊆ IR2) &rarr IR and Φ2 : (Ω2 ⊆ IR2) &rarr IR whose 0-level curves we want to match, we search for a diffeomorphism that minimizes the rate of change of the difference in tangential orientation of the zero-level sets. To make the formulation symmetric and to simplify computations, we map the domains of the level-set functions Φi to a common domain Ω by initial diffeomorphisms that are chosen arbitrarily. We then search for diffeomorphisms from Ω to itself, generating them by flows of certain vector fields on Ω. The resulting correspondences are scale- and rotation-invariant with respect to the curves. We show how this model can be used as a basis to compare curves of different topology. The model was tested on synthetic and MRI cardiac data,with good results. © Springer-Verlag Berlin Heidelberg 2005.

关键词： variational techniques

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Lens distortion calibration using level sets

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3rd International workshop on variational, Geometric, and level set methods in computer vision, VLSM 2005

作者： El-Melegy, Moumen T. Al-Ashwal, Nagi H. Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)3540293485

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide-angle lenses. Our approach is based on the analysis of distorted images of straight lines. We use a PDE-based level set method to find the lens distortion parameters that straighten these lines. One advantage of this method is that it integrates the extraction of image distorted lines and the computation of distortion parameters within one energy functional which is minimized during level set evolution. Some experiments to evaluate the performance of this approach are reported. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Lenses

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Energy minimization based segmentation and denoising using a multilayer level set approach

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5th International workshop on Energy Minimization methods in computer vision and Pattern Recognition, EMMCVPR 2005

作者： Chung, Ginmo Vese, Luminita A. Department of Mathematics University of California Los Angeles 405 Hilgard Avenue Los Angeles CA 90095-1555 United States

ISBN: (纸本)3540302875

This paper is devoted to piecewise-constant segmentation of images using a curve evolution approach in a variational formulation. The problem to be solved is also called the minimal partition problem, as formulated by Mumford and Shah [20]. The proposed new models are extensions of the techniques previously introduced in [9], [10], [27]. We represent here the set of boundaries of the segmentation implicitly, by a multilayer of level-lines of a continuous function. In the standard approach of front propagation, only one level line is used to represent the boundary. The multilayer idea is inspired from previous work on island dynamics for epitaxial growth [14], [4]. Using a multilayer level set approach, the computational cost is smaller and in some applications, a nested structure of the level lines can be useful. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image segmentation

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variational, Geometric, and level set methods in computer vision 2005

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丛书名： Lecture Notes in computer Science

2005年

作者： Nikos Paragios Olivier Faugeras Tony Chan Christoph Schnoerr

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Entropy controlled gauss-Markov random measure field models for early vision

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3rd International workshop on variational, Geometric, and level set methods in computer vision, VLSM 2005

作者： Rivera, Mariano Ocegueda, Omar Marroquin, Jose L. Centro de Investigacion en Matematicas A.C. Guanajuato Gto 36000 Mexico

ISBN: (纸本)3540293485

We present a computationally efficient segmentation-restoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the parameters of the feature generator models (restoration). Our algorithm computes an estimation of the posterior marginal probability distributions of the label field based on a Gauss Markov Random Measure Field model. Our proposal introduces an explicit entropy control for the estimated posterior marginals, therefore it improves the parameter estimation step. If the model parameters are given, our algorithm computes the posterior marginals as the global minimizers of a quadratic, linearly constrained energy function;therefore, one can compute very efficiently the optimal (Maximizer of the Posterior Marginals or MPM) estimator for multi-class segmentation problems. Moreover, a good estimation of the posterior marginals allows one to compute estimators different from the MPM for restoration problems, denoising and optical flow computation. Experiments demonstrate better performance over other state of the art segmentation approaches. © Springer-Verlag Berlin Heidelberg 2005.

关键词： computer vision

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Towards PDE-based image compression

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3rd International workshop on variational, Geometric, and level set methods in computer vision, VLSM 2005

作者： Galić, Irena Weickert, Joachim Welk, Martin Bruhn, Andrés Belyaev, Alexander Seidel, Hans-Peter Mathematical Image Analysis Group Faculty of Math and Computer Science Saarland University 66041 Saarbrücken Germany Max-Planck Institute for Informatics Stuhlsatzenhausweg 85 66123 Saarbrücken Germany

ISBN: (纸本)3540293485

While methods based on partial differential equations (PDEs) and variational techniques are powerful tools for denoising and inpainting digital images, their use for image compression was mainly focussing on pre- or post-processing so far. In our paper we investigate their potential within the decoding step. We start with the observation that edge-enhancing diffusion (BED), an anisotropic nonlinear diffusion filter with a diffusion tensor, is well-suited for scattered data interpolation: Even when the interpolation data are very sparse, good results are obtained that respect discontinuities and satisfy a maximum-minimum principle. This property is exploited in our studies on PDE-based image compression. We use an adaptive triangulation method based on B-tree coding for removing less significant pixels from the image. The remaining points serve as scattered interpolation data for the EED process. They can be coded in a compact and elegant way that reflects the B-tree structure. Our experiments illustrate that for high compression rates and non-textured images, this PDE-based approach gives visually better results than the widely-used JPEG coding. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image compression

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics: Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2005年 3752 LNCS卷 V页

作者： Paragios, Nikos Faugeras, Olivier Chan, Tony Schnoerr, Christoph

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Adaptive region-based video registration

Adaptive region-based video registration

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ieee workshop on Motion and Video Computing, MOTION 2005

作者： Xiao, Jiangjian Zhang, Yunjun Shah, Mubarak Computer Vision Lab. School of Computer Science University of Central Florida Orlando FL 32816 United States

ISBN: (纸本)0769522718

Video registration without meta data (camera location, viewing angles, and reference DEMs) is still a challenging problem. With the aim of handling this kind of problem, this paper presents an adaptive region expansion approach to propagate the alignment process from high confidence areas (reliable salient features) to low confidence areas and to simultaneously remove outlier regions. Hence, we re-cast the image registration problem as a partitioning problem such that we determine the optimal supporting regions and their corresponding motion parameters for the registration. First, we determine sparse robust correspondences between mission and reference images by using our wide baseline algorithm. Next, starting from the seed regions, the aligned areas are expanded to the whole overlapping areas using the graph cut algorithm, which is controlled by the level set representation of the previous region shape. Consequently, a robust video registration is achieved if the scene can be represented by one homography. Furthermore, we extend this approach to multi-homography video registration problem for 3D scenes, which cannot be directly solved by the current alignment methods. Using our motion layer extraction algorithm, the mission video first is segmented into several layers, then each layer is respectively aligned to the reference image by employing the region expansion algorithm. Several examples are demonstrated in the experiments to show that our approach is effective and robust.

关键词： Image registration

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Visibility constrained surface evolution

Visibility constrained surface evolution

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Conference on computer vision and Pattern Recognition (CVPR)

作者： J.E. Solem F. Kahl A. Heyden Applied Mathematics Group School of Technology and Society Malmö University Sweden Department of Computer Science & Engineering University of California La Jolla CA USA

关键词： Surface fitting Surface reconstruction Layout level set Image reconstruction Topology Cameras Clouds Mathematics computer science

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