TY - GEN
T1 - A new AdaboostSVM algorithm based on multi-feature fusion for multi-pose face detection
AU - Guo, Song
AU - Gu, Guochang
AU - Liu, Haibo
AU - Shen, Jing
AU - Cai, Zesu
PY - 2010
Y1 - 2010
N2 - To improve the performance of multi-pose face detection, the AdaboostSVM algorithm based on multi-feature fusion is proposed in this paper. Firstly, the Haar-like features and the triangular integral features are introduced and the edge-orientation field features based on morphological gradient are presented. Then, the AdaboostSVM Algorithm based on the above three kinds of features is proposed. The results of the experiment show that the proposed algorithm could improve the performance of multi-pose face detection effectively.
AB - To improve the performance of multi-pose face detection, the AdaboostSVM algorithm based on multi-feature fusion is proposed in this paper. Firstly, the Haar-like features and the triangular integral features are introduced and the edge-orientation field features based on morphological gradient are presented. Then, the AdaboostSVM Algorithm based on the above three kinds of features is proposed. The results of the experiment show that the proposed algorithm could improve the performance of multi-pose face detection effectively.
KW - AdaboostSVM
KW - Edge-orientation field features
KW - Morphological gradient
KW - Multi-feature fusion
KW - Multi-pose face detection
UR - https://www.scopus.com/pages/publications/78650563313
U2 - 10.1109/CISP.2010.5647904
DO - 10.1109/CISP.2010.5647904
M3 - 会议稿件
AN - SCOPUS:78650563313
SN - 9781424465149
T3 - Proceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
SP - 1735
EP - 1739
BT - Proceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
T2 - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Y2 - 16 October 2010 through 18 October 2010
ER -