TY - GEN
T1 - Gaussian decomposition for robust face recognition
AU - Sakaue, Fumihiko
AU - Shakunaga, Takeshi
PY - 2006/6/15
Y1 - 2006/6/15
N2 - This paper discusses Gaussian decomposition of facial images for robust recognition. While it cannot sufficiently extract an effective component, it can decompose an image into two effective components, the filtered image and its residual. The Gaussian component represents rough information for a lighting condition and small individuality. The residual represents individuality and the other information including small noise. The two components complement each other and they are evaluated independently in the framework of eigenface method. The image decomposition can also collaborate with parallel partial projections for robust recognition.
AB - This paper discusses Gaussian decomposition of facial images for robust recognition. While it cannot sufficiently extract an effective component, it can decompose an image into two effective components, the filtered image and its residual. The Gaussian component represents rough information for a lighting condition and small individuality. The residual represents individuality and the other information including small noise. The two components complement each other and they are evaluated independently in the framework of eigenface method. The image decomposition can also collaborate with parallel partial projections for robust recognition.
UR - http://www.scopus.com/inward/record.url?scp=33744957386&partnerID=8YFLogxK
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U2 - 10.1007/11612032_12
DO - 10.1007/11612032_12
M3 - Conference contribution
AN - SCOPUS:33744957386
SN - 3540312196
SN - 9783540312192
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 110
EP - 119
BT - Computer Vision - ACCV 2006 - 7th Asian Conference on Computer Vision, Proceedings
T2 - 7th Asian Conference on Computer Vision, ACCV 2006
Y2 - 13 January 2006 through 16 January 2006
ER -