Reference : Statistical Analysis of the Global Geodesic Function for 3D Object Classification
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/8044
Statistical Analysis of the Global Geodesic Function for 3D Object Classification
English
Aouada, Djamila mailto [Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA]
Feng, Shuo [Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA]
Krim, Hamid [Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA]
2007
IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007
645- 648
Yes
International
1-4244-0727-3
ICASSP 2007
from 15-04-2007 to 20-04-2007
Honolulu
HI
[en] This paper presents a novel classification strategy for 3D objects. Our technique is based on using a global geodesic function to intrinsically describe the surface of an object. The choice of the global geodesic function ensures the invariance of the classification procedure to scaling and all isometric transformations. Using the Jensen-Shannon divergence, feature parameters are extracted from the probability distribution functions of the global geodesic function for each one of the classes. These parameters are used in the decision of a class membership of an object. This approach demonstrates low computational cost, efficiency, and robustness to resolution over many different data sets.
http://hdl.handle.net/10993/8044
10.1109/ICASSP.2007.365990
IEEE International Conference on Acoustics, Speech and Signal Processing, 2007.

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