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

Volume

4

fYear

2010

fDate

16-18 Oct. 2010

Firstpage

1735

Lastpage

1739

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2010 3rd International Congress on

Conference_Location

Yantai

Print_ISBN

978-1-4244-6513-2

Type

conf

DOI

10.1109/CISP.2010.5647904

Filename

5647904