Title :
A new AdaboostSVM algorithm based on multi-feature fusion for multi-pose face detection
Author :
Guo, Song ; Gu, Guochang ; Liu, Haibo ; Shen, Jing ; Cai, Zesu
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Abstract :
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.
Keywords :
Haar transforms; edge detection; face recognition; feature extraction; sensor fusion; support vector machines; AdaboostSVM algorithm; Haar-like features; edge-orientation field features; morphological gradient; multi-feature fusion; multi-pose face detection; triangular integral features; Classification algorithms; Face; Face detection; Feature extraction; Image edge detection; Noise; Training; AdaboostSVM; Multi-pose face detection; edge-orientation field features; morphological gradient; multi-feature fusion;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5647904
