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2006 IEEE International Conference on Multimedia and Expo
Face Recognition using 3D Summation Invariant Features
Toronto, ON, Canada
July 09-July 12
ISBN: 1-4244-0366-7
ASCII Text
x 
 
Wei-yang Lin, Kin-chung wong, Yu Hu, Nigel Boston, "Face Recognition using 3D Summation Invariant Features," Multimedia and Expo, IEEE International Conference on, pp. 1733-1736, 2006 IEEE International Conference on Multimedia and Expo, 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICME.2006.262885,
author = {Wei-yang Lin and Kin-chung wong and Yu Hu and Nigel Boston},
title = {Face Recognition using 3D Summation Invariant Features},
journal ={Multimedia and Expo, IEEE International Conference on},
volume = {0},
year = {2006},
isbn = {1-4244-0366-7},
pages = {1733-1736},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICME.2006.262885},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Multimedia and Expo, IEEE International Conference on
TI - Face Recognition using 3D Summation Invariant Features
SN - 1-4244-0366-7
SP1733
EP1736
A1 - Wei-yang Lin,
A1 - Kin-chung wong,
A1 - Yu Hu,
A1 - Nigel Boston,
PY - 2006
KW - null
VL - 0
JA - Multimedia and Expo, IEEE International Conference on
ER -
 
Wei-yang Lin, University of Wisconsin-Madison, Department of Electrical and Computer Engineering, 1415 Engineering Drive, Madison WI, 53706 USA. weiyanglin@wisc.edu
Kin-chung wong, University of Wisconsin-Madison, Department of Electrical and Computer Engineering, 1415 Engineering Drive, Madison WI, 53706 USA
Yu Hu, University of Wisconsin-Madison, Department of Electrical and Computer Engineering, 1415 Engineering Drive, Madison WI, 53706 USA
Nigel Boston, University of Wisconsin-Madison, Department of Electrical and Computer Engineering, 1415 Engineering Drive, Madison WI, 53706 USA
In this paper, we developed a family of 2D and 3D invariant features with applications to 3D human faces recognition. The main contributions of this paper are: (a) systematically deriving a family of novel features, called summation invariant that are invariant to Euclidean transformation in both 2D and 3D; (b) developing an effective method to apply summation invariant to the 3D face recognition problem. Tested with the 3D data from the Face Recognition Grand Challenge v1.0 dataset, the proposed new features exhibit achieves a performance that rivals the best 3D face recognition algorithms reported so far.
Citation:
Wei-yang Lin, Kin-chung wong, Yu Hu, Nigel Boston, "Face Recognition using 3D Summation Invariant Features," icme, pp.1733-1736, 2006 IEEE International Conference on Multimedia and Expo, 2006
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