Titlebook: Computer Vision - ECCV 2002; 7th European Confere Anders Heyden,Gunnar Sparr,Peter Johansen Conference proceedings 2002 Springer-Verlag Ber

閃光東本

A Markov Chain Monte Carlo Approach to Stereovisiond up the computation. The efficiency of the algorithm is demonstrated, and we illustrate our method with the computation of confidence intervals and probability maps of large errors, which may be applied to optimize a trajectory in a three dimensional environment.

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墊子

Wallow

Approximate Thin Plate Spline Mappings applications. Unfortunately the solution requires the inversion of a . matrix, where . is the number of points in the data set, thus making it impractical for large scale applications. As it turns out, a surprisingly good approximate solution is often possible using only a small subset of correspon

Etching

DEFORMOTION Deforming Motion, Shape Average and the Joint Registration and Segmentation of Imageshe more general deformation (a diffeomorphism)? In this paper we propose a definition of motion for a deforming object and introduce a notion of “shape average” as the entity that separates the motion from the deformation. Our definition allows us to derive novel and efficient algorithms to register

Keshan-disease

invade

What Energy Functions Can Be Minimized via Graph Cuts?f these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet because these graph constructions are complex and highly specific to a particular energy function, graph cuts have seen limited application to date. In this paper we characterize the energy fu

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Multi-camera Scene Reconstruction via Graph Cutseconstruction is a natural generalization of the stereo matching problem. However, it is much more difficult than stereo, primarily due to the difficulty of reasoning about visibility. In this paper, we take an approach that has yielded excellent results for stereo, namely energy minimization via gr

malign

A Markov Chain Monte Carlo Approach to Stereovisioncessing stage, i.e. once the disparity map has been computed, and suppose that the only information available is the stereoscopic pair. The method, which consists of sampling from the posterior distribution given the stereoscopic pair, allows the prediction of large errors which occur with low proba

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