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Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomáš Pajdla,Jiří Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

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楼主: INFER
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Robust Fitting by Adaptive-Scale Residual Consensus parameters of a model, and ii) differentiate inliers from outliers. We propose a new estimator called Adaptive-Scale Residual Consensus (ASRC). ASRC scores a model based on both the residuals of inliers and the corresponding scale estimate determined by those inliers. ASRC is very robust to multipl
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An Adaptive Window Approach for Image Smoothing and Structures Preservingant modeling of the image with an adaptive choice of a window around each pixel. The adaptive smoothing technique associates with each pixel the weighted sum of data points within the window. We describe a statistical method for choosing the optimal window size, in a manner that varies at each pixel
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Are Iterations and Curvature Useful for Tensor Voting? on tensor voting are presented. First the use of iterations is investigated, and second, a new method for integrating curvature information is evaluated. In opposition to other grouping methods, tensor voting claims the advantage to be non-iterative. Although non-iterative tensor voting methods pro
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Shape Matching and Recognition – Using Generative Models and Informative Featurese model allows for a class of transformations, such as affine and non-rigid transformations, and induces a similarity measure between shapes. The matching process is formulated in the EM algorithm. To have a fast algorithm and avoid local minima, we show how the EM algorithm can be approximated by u
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Recognizing Objects in Range Data Using Regional Point Descriptors successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizing vehicles in range scans of scenes using a database
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