TY - GEN
T1 - Local kernel mapping for object recognition
AU - Zhang, Baochang
AU - Zheng, Hong
AU - Wang, Zhongli
PY - 2009
Y1 - 2009
N2 - This paper proposes a new method, named Local Kernel Mapping (LKM), for object recognition. LKM is proposed to capture the nonlinear local relationship by using the kernel function. Different from traditional kernel methods for feature extraction, the proposed method does not need to reserve the training samples. To testify the effectiveness of LKM, we apply it on Local Binary Pattern (LBP), and the experiment results on palmprint show that LKM can improve the performance of the LBP method.
AB - This paper proposes a new method, named Local Kernel Mapping (LKM), for object recognition. LKM is proposed to capture the nonlinear local relationship by using the kernel function. Different from traditional kernel methods for feature extraction, the proposed method does not need to reserve the training samples. To testify the effectiveness of LKM, we apply it on Local Binary Pattern (LBP), and the experiment results on palmprint show that LKM can improve the performance of the LBP method.
UR - https://www.scopus.com/pages/publications/77950610079
U2 - 10.1109/ICNC.2009.419
DO - 10.1109/ICNC.2009.419
M3 - 会议稿件
AN - SCOPUS:77950610079
SN - 9780769537368
T3 - 5th International Conference on Natural Computation, ICNC 2009
SP - 573
EP - 576
BT - 5th International Conference on Natural Computation, ICNC 2009
T2 - 5th International Conference on Natural Computation, ICNC 2009
Y2 - 14 August 2009 through 16 August 2009
ER -