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Proceedings Paper

Graph-based 3D object classification
Author(s): Sajjad Baloch; Hamid Krim
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Paper Abstract

In this paper, we propose a novel method for the classification of 3D shapes, based on topo-geometric shape descriptors. Topo-geometric models have an advantage over existing shape descriptors that they capture complete shape information - capturing topology through skeletal graphs, and geometry via edge weights. The resulting weighted graph representation allows shape classification by establishing error correcting subgraph isomorphisms between the test graph and model graphs, where the best match is the one that corresponds to largest subgraph isomorphism. We propose various cost assignments for graph edit operations for error correction, which in turn takes into account any shape variations arising due to noise and measurement errors.

Paper Details

Date Published: 2 February 2006
PDF: 9 pages
Proc. SPIE 6065, Computational Imaging IV, 606505 (2 February 2006); doi: 10.1117/12.659603
Show Author Affiliations
Sajjad Baloch, North Carolina State Univ. (United States)
Hamid Krim, North Carolina State Univ. (United States)


Published in SPIE Proceedings Vol. 6065:
Computational Imaging IV
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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