Vladislav Golyanik

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The problem of dense point set registration, given a sparse set of prior correspondences, often arises in computer vision tasks. Unlike in the rigid case, integrating prior knowledge into a registration algorithm is especially demanding in the non-rigid case due to the high variability of motion and deformation. In this paper we present the Extended(More)
We present an elegant solution to joint pre-alignment and rigid point set registration, given prior matches. Instead of performing pre-alignment and the actual registration in the separate steps, prior matches explicitly influence the registration procedure in our approach. This results in several advantages. Firstly, our approach solves the pre-alignment(More)
In this paper a new astrodynamics inspired rigid point set registration algorithm is introduced-the Gravitational Approach (GA). We formulate point set registration as a modified N-body problem with additional constraints and obtain an algorithm with unique properties which is fully scalable with the number of processing cores. In GA, a template point set(More)
This paper addresses the problem of video registration for dense non-rigid structure from motion under suboptimal conditions, such as noise, self-occlusions, considerable external occlusions or specularities, i.e. the computation of optical flow between the reference image and each of the subsequent images in a video sequence when the camera observes a(More)
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