Motivated by the increasing availability of 3D sensors capable of delivering both shape and texture information, this paper presents a novel descriptor for feature matching in 3D data enriched with texture. The proposed approach stems from the theory of a recently proposed descriptor for 3D data which relies on shape only, and represents its generalization to the case of multiple cues associated with a 3D mesh. The proposed descriptor, dubbed CSHOT, is demonstrated to notably improve the accuracy of feature matching in challenging object recognition scenarios characterized by the presence of clutter and occlusions.

A combined texture-shape descriptor for enhanced 3D feature matching

TOMBARI, FEDERICO;SALTI, SAMUELE;DI STEFANO, LUIGI
2011

Abstract

Motivated by the increasing availability of 3D sensors capable of delivering both shape and texture information, this paper presents a novel descriptor for feature matching in 3D data enriched with texture. The proposed approach stems from the theory of a recently proposed descriptor for 3D data which relies on shape only, and represents its generalization to the case of multiple cues associated with a 3D mesh. The proposed descriptor, dubbed CSHOT, is demonstrated to notably improve the accuracy of feature matching in challenging object recognition scenarios characterized by the presence of clutter and occlusions.
Proceedings of the 18th IEEE International Conference on Image Processing
809
812
F. Tombari; S. Salti; L. Di Stefano
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/106074
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