DocumentCode :
3381408
Title :
Statistical model for human face detection using multi-resolution features
Author :
Ying, Zhengrong ; Castanon, David
Author_Institution :
Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA
fYear :
1999
fDate :
1999
Firstpage :
560
Lastpage :
563
Abstract :
A novel method for face detection is presented, which is robust to face, illumination, and pose variations. This method is based on processing of image features constructed using multi-resolution techniques, and using statistical models of these multi-resolution features to detect the presence of faces in an image. Simulation results show that the new method significantly outperforms traditional methods based on normalized correlation of images with an average face
Keywords :
face recognition; feature extraction; image texture; statistical analysis; average face; human face detection; image features; multi-resolution features; multi-resolution techniques; normalized correlation; pose variations; statistical model; statistical models; Computer vision; Face detection; Face recognition; Feature extraction; Filters; Humans; Layout; Lighting; Reactive power; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on
Conference_Location :
Bethesda, MD
Print_ISBN :
0-7695-0446-9
Type :
conf
DOI :
10.1109/ICIIS.1999.810347
Filename :
810347
Link To Document :
بازگشت