@Article{NMTMA-6-199,
author = {Artiom Kovnatsky, Dan Raviv, Michael M. Bronstein, Alexander M. Bronstein and Ron Kimmel},
title = {Geometric and Photometric Data Fusion in Non-Rigid Shape Analysis},
journal = {Numerical Mathematics: Theory, Methods and Applications},
year = {2013},
volume = {6},
number = {1},
pages = {199--222},
abstract = {<p style="text-align: justify;">In this paper, we explore the use of the diffusion geometry framework for the
fusion of geometric and photometric information in local and global 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.</p>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2013.mssvm11},
url = {http://global-sci.org/intro/article_detail/nmtma/5900.html}
}