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