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Surface feature detection and description with applications to mesh matching

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4 Author(s)
Andrei Zaharescu ; Perception Team, INRIA Grenoble Rhône-Alpes, 655 Avenue de l'Europe, Montbonnot, 38 334 Saint Ismier Cedex, France ; Edmond Boyer ; Kiran Varanasi ; Radu Horaud

In this paper we revisit local feature detectors/descriptors developed for 2D images and extend them to the more general framework of scalar fields defined on 2D manifolds. We provide methods and tools to detect and describe features on surfaces equiped with scalar functions, such as photometric information. This is motivated by the growing need for matching and tracking photometric surfaces over temporal sequences, due to recent advancements in multiple camera 3D reconstruction. We propose a 3D feature detector (MeshDOG) and a 3D feature descriptor (MeshHOG) for uniformly triangulated meshes, invariant to changes in rotation, translation, and scale. The descriptor is able to capture the local geometric and/or photometric properties in a succinct fashion. Moreover, the method is defined generically for any scalar function, e.g., local curvature. Results with matching rigid and non-rigid meshes demonstrate the interest of the proposed framework.

Published in:

Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on

Date of Conference:

20-25 June 2009