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Visibility of noisy point cloud data

Mehra, R; Tripathi, P; Sheffer, A; Mitra, NJ; (2010) Visibility of noisy point cloud data. COMPUT GRAPH-UK , 34 (3) 219 - 230. 10.1016/j.cag.2010.03.002.

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We present a robust algorithm for estimating visibility from a given viewpoint for a point set containing concavities, non-uniformly spaced samples, and possibly corrupted with noise. Instead of performing an explicit surface reconstruction for the points set, visibility is computed based on a construction involving convex hull in a dual space, an idea inspired by the work of Katz et al. [26]. We derive theoretical bounds on the behavior of the method in the presence of noise and concavities, and use the derivations to develop a robust visibility estimation algorithm. In addition, computing visibility from a set of adaptively placed viewpoints allows us to generate locally consistent partial reconstructions. Using a graph based approximation algorithm we couple such reconstructions to extract globally consistent reconstructions. We test our method on a variety of 2D and 3D point sets of varying complexity and noise content. (C) 2010 Elsevier Ltd. All rights reserved.

Type: Article
Title: Visibility of noisy point cloud data
DOI: 10.1016/j.cag.2010.03.002
Keywords: Computer graphics, Point cloud, Visibility, Line and curve generation, Surface reconstruction, Noise smoothing, RECONSTRUCTION, CRUST, POWER
URI: http://discovery.ucl.ac.uk/id/eprint/1327989
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