TY - GEN
T1 - A novel matrix norm based Gaussian kernel for feature extraction of images
AU - Li, Jun Bao
AU - Chu, Shu Chuan
AU - Pan, Jeng Shyang
AU - Ho, Jiun Huei
PY - 2006/12/18
Y1 - 2006/12/18
N2 - Gaussian kernel is widely used in Support Vector Machines and many other kernel methods, and it is most often deemed to provide a local measure of similarity between vectors, which causes large storage requirements and large computational effort for transforming images to vectors owing to its viewing images as vectors. A novel matrix norm based Gaussian kernel (M-Gaussian kernel) which views images as matrices is proposed to solve the problem. Experiments conducted on ORL face database show the effectiveness of the proposed M-Gaussian kernel.
AB - Gaussian kernel is widely used in Support Vector Machines and many other kernel methods, and it is most often deemed to provide a local measure of similarity between vectors, which causes large storage requirements and large computational effort for transforming images to vectors owing to its viewing images as vectors. A novel matrix norm based Gaussian kernel (M-Gaussian kernel) which views images as matrices is proposed to solve the problem. Experiments conducted on ORL face database show the effectiveness of the proposed M-Gaussian kernel.
UR - http://www.scopus.com/inward/record.url?scp=40349100579&partnerID=8YFLogxK
U2 - 10.1109/IIH-MSP.2006.265004
DO - 10.1109/IIH-MSP.2006.265004
M3 - Conference contribution
AN - SCOPUS:40349100579
SN - 0769527450
SN - 9780769527451
T3 - Proceedings - 2006 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2006
SP - 305
EP - 308
BT - Proceedings - 2006 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2006
CY - United States of America
T2 - 2006 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2006
Y2 - 18 December 2006 through 20 December 2006
ER -