p-adic Methods in Stereo Vision
نویسنده
چکیده
The so-called essential matrix relates corresponding points of two images from the same scene in 3D, and allows to solve the relative pose problem for the two cameras up to a global scaling factor, if the camera calibrations are known. We will discuss how Hensel’s lemma from number theory can be used to find geometric approximations to solutions of the equations describing the essential matrix. Together with recent p-adic classification methods, this leads to RanSaCp , a p-adic version of the classical RANSAC in stereo vision. This approach is motivated by the observation that using p-adic numbers often leads to more efficient algorithms than their real or complex counterparts.
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تاریخ انتشار 2010