DocumentCode
2363840
Title
Learning a distribution-based face model for human face detection
Author
Sung, Kah-Kay ; Poggio, Tomaso
Author_Institution
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
fYear
1995
fDate
31 Aug-2 Sep 1995
Firstpage
398
Lastpage
406
Abstract
We present a distribution-based modeling cum example-based learning approach for detecting human faces in cluttered scenes. The distribution-based model captures complex variations in human face patterns that cannot be adequately described by classical pictorial template-based matching techniques or geometric model-based pattern recognition schemes. We also show how explicitly modeling the distribution of certain “facelike” nonface patterns can help improve classification results
Keywords
biometrics (access control); face recognition; image recognition; learning by example; statistical analysis; cluttered scenes; complex variations; distribution-based face model learning; example-based learning; facelike nonface patterns; human face detection; human face patterns; Biological system modeling; Context modeling; Distance measurement; Face detection; Humans; Layout; Learning; Pattern matching; Pixel; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing [1995] V. Proceedings of the 1995 IEEE Workshop
Conference_Location
Cambridge, MA
Print_ISBN
0-7803-2739-X
Type
conf
DOI
10.1109/NNSP.1995.514914
Filename
514914
Link To Document