Robust Topological Features for Deformation Invariant Image Matching
Edgar Lobaton, Ram Vasudevan, Ron Alterovitz and Ruzena Bajcsy
EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2011-89
August 5, 2011
http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-89.pdf
Local photometric descriptors are a crucial low level component of numerous computer vision algorithms. In practice, these descriptors are constructed to be invariant to a class of transformations. However, the development of a descriptor that is simultaneously robust to noise and invariant under general deformation has proven difficult. In this paper, we introduce the Topological-Attributed Relational Graph (T-ARG), a new local photometric descriptor constructed from homology that is provably invariant to locally bounded deformation. This new robust topological descriptor is backed by a formal mathematical framework. We apply T-ARG to a set of benchmark images to evaluate its performance. Results indicate that T-ARG significantly outperforms traditional descriptors for noisy, deforming images.
BibTeX citation:
@techreport{Lobaton:EECS-2011-89,
Author = {Lobaton, Edgar and Vasudevan, Ram and Alterovitz, Ron and Bajcsy, Ruzena},
Title = {Robust Topological Features for Deformation Invariant Image Matching},
Institution = {EECS Department, University of California, Berkeley},
Year = {2011},
Month = {Aug},
URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-89.html},
Number = {UCB/EECS-2011-89},
Abstract = {Local photometric descriptors are a crucial low level component of numerous computer vision algorithms. In practice, these descriptors are constructed to be invariant to a class of transformations. However, the development of a descriptor that is simultaneously robust to noise and invariant under general deformation has proven difficult. In this paper, we introduce the Topological-Attributed Relational Graph (T-ARG), a new local photometric descriptor constructed from homology that is provably invariant to locally bounded deformation. This new robust topological descriptor is backed by a formal mathematical framework. We apply T-ARG to a set of benchmark images to evaluate its performance. Results indicate that T-ARG significantly outperforms traditional descriptors for noisy, deforming images.}
}
EndNote citation:
%0 Report %A Lobaton, Edgar %A Vasudevan, Ram %A Alterovitz, Ron %A Bajcsy, Ruzena %T Robust Topological Features for Deformation Invariant Image Matching %I EECS Department, University of California, Berkeley %D 2011 %8 August 5 %@ UCB/EECS-2011-89 %U http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-89.html %F Lobaton:EECS-2011-89