Gravitational Approach for Point Set Registration

Vladislav Golyanik; Sk Aziz Ali; Didier Stricker

In: Proceedings of the International Conference on Computer Vision and Pattern Recognition |. International Conference on Computer Vision and Pattern Recognition (CVPR-16), June 26 - July 1, Las Vegas, NV, USA, Computer Vision Foundation (CVF), 2016.


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 moves in a viscous medium under gravitational forces induced by a reference point set. Pose updates are completed by numerically solving the differential equations of Newtonian mechanics. We discuss techniques for efficient implementation of the new algorithm and evaluate it on several synthetic and real-world scenarios. GA is compared with the widely used Iterative Closest Point and the state of the art rigid Coherent Point Drift algorithms. Experiments evidence that the new approach is robust against noise and can handle challenging scenarios with structured outliers.


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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence