Spectral analysis driven sparse matching of 3D shapes

Authors:
Tal Darom;Yosi Keller
Affiliations:
Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel;Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
Venue:
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
Year:
2012

Citing 8
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Abstract

In this work we present an approach for matching three-dimensional mesh objects related by isometric transfor- mations and scaling. We propose to utilize the Scale invariant Scale-DoG detector and Local Depth SIFT mesh descriptor, to derive a statistical voting-based scheme to robustly estimate the scale ratio between the registered meshes. This paves the way to formulating a novel non-rigid mesh registration scheme, by matching sets of sparse salient feature points using spectral graph matching. The resulting approach is shown to compare favorably with previous state-of-the-art approaches in registering meshes related by partial alignment, while being a few orders of magnitude faster.