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)
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)
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)
The paper introduces an accurate solution to dense orthographic Non-Rigid Structure from Motion (NRSfM) in scenarios with severe occlusions or, likewise, inaccurate correspondences. We integrate a shape prior term into variational optimisation framework. It allows to penalize irregularities of the time-varying structure on the per-pixel level if(More)
Alignment of 3D human body scans is a challenging problem in computer vision with various applications. While being extensively studied for the mesh-based case, it is still involved if scans lack topology. In this paper, we propose a practical solution to the point cloud based registration of 3D human scans and a 3D human template. We adopt recent advances(More)
In this paper, we show how to minimise a quadratic function on a set of orthonormal matrices using an efficient semidefinite programming solver with application to dense non-rigid structure from motion. Thanks to the proposed technique, a new form of the convex relaxation for the Metric Projections (MP) algorithm is obtained. The modification results in an(More)
Recovery of scene flow (a dense 3D velocity vector field) of a dynamic scene from monocular image sequences is an emerging field in computer vision. Being sensitive to occlusions, existing Monocular Scene Flow (MSF) methods are either limited in handling non-rigid deformations [5], or make strong assumptions on scene [2] and camera motion [1]. To overcome(More)
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