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Binary descriptor based on heat diffusion for Non-rigid shape analysis
Journal article   Peer reviewed

Binary descriptor based on heat diffusion for Non-rigid shape analysis

X. Wang, F. Sohel, M. Bennamoun and H. Lei
Lecture Notes in Computer Science, Vol.9431, pp.751-761
7th Pacific Rim Symposium on Image and Video Technology (PSIVT) 2015 (Auckland, New Zealand, 23/11/2015–27/11/2015)
2015
DOI: https://doi.org/10.1007/978-3-319-29451-3_59
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Abstract

Non-rigid shape analysis Local descriptor Heat diffusion Binary descriptor
This paper presents an efficient feature point descriptor for non-rigid shape analysis. The descriptor is developed based on the properties of the heat diffusion process on a shape. We use, for the first time, the Heat Kernel Signature of a particular time scale to define the scalar field on a manifold. Then, motivated by the successful use of a local reference frame for rigid shape analysis, we construct a repetitive local polar coordinate system, which is invariant under isometric deformations. Finally, a binary descriptor is derived by comparing the intensities of the neighboring points for each feature point. We show that the descriptor is highly discriminative and can be computed simply using ‘intensity comparisons’ on a shape. Furthermore, its similarity can be evaluated using the Hamming distance, which is very efficient to compute compared with the commonly used L2 norm. Our experiments demonstrate a superior performance compared to existing techniques on the standard benchmark TOSCA.

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