TY - GEN
T1 - Photometric heat kernel signatures
AU - Kovnatsky, Artiom
AU - Bronstein, Michael M.
AU - Bronstein, Alexander M.
AU - Kimmel, Ron
PY - 2012
Y1 - 2012
N2 - In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local heat kernel signature shape descriptors. Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information. Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.
AB - In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local heat kernel signature shape descriptors. Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information. Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.
UR - http://www.scopus.com/inward/record.url?scp=84855706680&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-642-24785-9_52
DO - https://doi.org/10.1007/978-3-642-24785-9_52
M3 - منشور من مؤتمر
SN - 9783642247842
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 616
EP - 627
BT - Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers
T2 - 3rd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011
Y2 - 29 May 2011 through 2 June 2011
ER -