Surface Feature Detection and Description with Applications to Mesh Matching

Andrei Zaharescu 1 Edmond Boyer 1 Kiran Varanasi 1 Radu Horaud 1
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : 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 rigid and non-rigid mesh matching demonstrate the interest of the proposed framework.
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Andrei Zaharescu, Edmond Boyer, Kiran Varanasi, Radu Horaud. Surface Feature Detection and Description with Applications to Mesh Matching. CVPR 2009 - IEEE International Conference on Computer Vision and Pattern Recognition, Jun 2009, Miami, United States. pp.373-380, ⟨10.1109/CVPR.2009.5206748⟩. ⟨inria-00440407⟩

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