Minas E. Spetsakis

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A theory is presented for the computation of three dimensional motion and structure from dynamic imagery, using only line correspondences. The traditional approach of corresponding microfeatures (interesting points-highlights, corners, high curvature points, etc.) is reviewed and its shortcomings are discussed. Then, a theory is presented that describes a(More)
We analyze the problem of estimating 3-D motion in an optimal manner using correspondences of features in two views. The importance of having an optimal estimator is twofold: first, for the estimation itself and, second, for the bound it offers on how much sensitivity one can expect from a two-frame, point-based motion algorithm. The optimal estimator turns(More)
We present a new algorithm that does motion segmentation by tracking small textured patches and then clustering them using EM. A small patch has the advantage that its motion is well modeled by uniform flow and runs a lower risk of boundary inclusion. Inherently, a small patch has less data so it is more susceptible to noise and it is not well suited to fit(More)
Many Computer Vision algorithms employ the sum of pixel-wise squared differences between two patches as a statistical measure of similarity. This silently assumes that the noise in every pixel is independent. We present a method that involves a much more general noise model with relaxed independence assumptions but without significant increase in the(More)