A Riemannian Framework for Matching Point Clouds Represented by the Schrödinger Distance Transform

In this paper, we cast the problem of point cloud matching as a shape matching problem by transforming each of the given point clouds into a shape representation called the Schrödinger distance transform (SDT) representation. This is achieved by solving a static Schrödinger equation instead of the...

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Bibliographic Details
Published in:	2014 IEEE Conference on Computer Vision and Pattern Recognition Vol. 2014; pp. 3756 - 3761
Main Authors:	Yan Deng, Rangarajan, Anand, Eisenschenk, Stephan, Vemuri, Baba C.
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01.06.2014
Subjects:	Algorithms Data models Density Equations Exact solutions Matching Mathematical analysis Measurement non-rigid registration Optimization Point clouds matching Representations Riemannian Manifold Schrodinger Distance Transform Schroedinger equation Shape Three dimensional models Three-dimensional displays Transformations Transforms Unit Hilbert Sphere
ISSN:	1063-6919, 1063-6919
Online Access:	Get full text
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