CSC 329 Chapter Notes -Higher-Order Singular Value Decomposition, Tensor Field, Signal-To-Noise Ratio
21 Nov 2013
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Institute for robotics & intelligent systems computer science department. Each site collects all the votes cast at its location and encodes them into a new tensor. A local, parallel marching process then simultaneously detects features. The proposed approach is very different from traditional variational approaches, as it is non-iterative. Further- more, the only free parameter is the size of the neigh- borhood, related to the scale. We have developed several algorithms based on the proposed methodology to address a number of early vision problems, including perceptual grouping in 2-d and 3-d, shape from stereo, and motion grouping and segmentation, and the results are very encouraging. In computer vision, we often face the problem of identifying salient and structured information in a noisy data set. From greyscale images, edges are extracted by first detecting subtle local changes in intensity and then linking locations based on the noisy signal responses.
