TY - GEN
T1 - Multi-view face recognition via joint dynamic sparse representation
AU - Zhang, Haichao
AU - Nasrabadi, Nasser M.
AU - Huang, Thomas S.
AU - Zhang, Yanning
PY - 2011
Y1 - 2011
N2 - We consider the problem of automatically recognizing a human face from its multi-view images with unconstrained poses and illuminations. We formulate the multi-view face recognition problem as that of classifying among several multi-input (views) regression models by using a novel joint dynamic sparse representation method which exploits jointly the inter-correlation among all the multi-view images in order to make a decision. Extensive experiments on CMU Multi-PIE face database are conducted to verify the efficacy of the proposed method.
AB - We consider the problem of automatically recognizing a human face from its multi-view images with unconstrained poses and illuminations. We formulate the multi-view face recognition problem as that of classifying among several multi-input (views) regression models by using a novel joint dynamic sparse representation method which exploits jointly the inter-correlation among all the multi-view images in order to make a decision. Extensive experiments on CMU Multi-PIE face database are conducted to verify the efficacy of the proposed method.
KW - joint dynamic sparsity
KW - multi-view face recognition
KW - sparse representation based classification
UR - http://www.scopus.com/inward/record.url?scp=84863055716&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2011.6116301
DO - 10.1109/ICIP.2011.6116301
M3 - 会议稿件
AN - SCOPUS:84863055716
SN - 9781457713033
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 3025
EP - 3028
BT - ICIP 2011
T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011
Y2 - 11 September 2011 through 14 September 2011
ER -