Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomá? Pajdla,Ji?í Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

FIR

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

Resistance

尾巴

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

indifferent

貪婪的人

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

荒唐

流動(dòng)性

CANDY

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

Generalize

啜泣

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