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We present a novel framework for detection, tracking and recognition of deformable objects undergoing geometric and radiometric transformations. Assuming the geometric deformations an object undergoes, belong to some finite dimensional family, it has been shown that the universal manifold embedding (UME) provides a set of nonlinear operators that universally maps each of the different manifolds, where...
In this work, we present a novel scheme for accurate affine transformation estimation that enables locating large amount of point matches with high geometric precision and low rate of false matches. We show that this is achievable in low computational demand. Point matching is one of the most fundamental tasks in computer vision. It is being extensively used in popular applications like object detection,...
In this work, we present a novel method for accurate affine transformation estimation of image regions. We illustrate the benefits of using such a method in a point matching mechanism that enables locating large amount of point matches with high geometric precision and low rate of false matches. Recent publications have shown that considering the affine transformation model of local regions, is extremely...
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