DocumentCode :
3491522
Title :
Real time face recognition system using autoassociative neural network models
Author :
Palanivel, S. ; Venkatesh, B.S. ; Yegnanarayana, B.
Author_Institution :
Dept. of Comput. Sci. & Eng., Indian Inst. of Technol. Madras, Chennai, India
Volume :
2
fYear :
2003
fDate :
6-10 April 2003
Abstract :
This paper proposes a novel method for video-based real time face recognition. The proposed method uses motion information to detect the face region, and the region is processed in YCrCb color space to determine the location of the eyes. The system extracts only the gray level features relative to the location of the eyes. autoassociative neural network (AANN) model is used to capture the distribution of the extracted gray level features. Experimental results show that the proposed system gives an average recognition rate of 99% in real time for 25 subjects. The performance of the proposed method is invariant to size, tilt of the face and is also not sensitive to natural lighting conditions.
Keywords :
face recognition; image colour analysis; neural nets; real-time systems; video signal processing; AANN model; autoassociative neural network models; automatic human faces recognition; average recognition rate; color space; eyes location; gray level features extraction; natural lighting conditions; video-based real time face recognition; Data mining; Eyes; Face detection; Face recognition; Head; Neural networks; Pixel; Real time systems; Skin; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-7663-3
Type :
conf
DOI :
10.1109/ICASSP.2003.1202496
Filename :
1202496
Link To Document :
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