Uncontrolled face recognition by individual stable neural network

Geng, Xin, Zhou, Zhi-Hua and Dai, Honghua 2006, Uncontrolled face recognition by individual stable neural network, Lecture notes in computer science, vol. 4099, pp. 553-562.

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Title Uncontrolled face recognition by individual stable neural network
Author(s) Geng, Xin
Zhou, Zhi-Hua
Dai, Honghua
Journal name Lecture notes in computer science
Volume number 4099
Start page 553
End page 562
Publisher Springer-Verlag
Place of publication Berlin , Germany
Publication date 2006
ISSN 0302-9743
1611-3349
Summary There usually exist diverse variations in face images taken under uncontrolled conditions. Most previous work on face recognition focuses on particular variations and usually assume the absence of others. Such work is called controlled face recognition. Instead of the ‘divide and conquer’ strategy adopted by controlled face recognition, this paper presents one of the first attempts directly aiming at uncontrolled face recognition. The solution is based on Individual Stable Neural Network (ISNN) proposed in this paper. ISNN can map a face image into the so-called Individual Stable Space (ISS), the feature space that only expresses personal characteristics, which is the only useful information for recognition. There are no restrictions for the face images fed into ISNN. Moreover, unlike many other robust face recognition methods, ISNN does not require any extra information (such as view angle) other than the personal identities during training. These advantages of ISNN make it a very practical approach for uncontrolled face recognition. In the experiments, ISNN is tested on two large face databases with vast variations and achieves the best performance compared with several popular face recognition techniques.
Notes The original publication can be found at www.springerlink.com
Language eng
Field of Research 080104 Computer Vision
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2006, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30003699

Document type: Journal Article
Collection: School of Engineering and Technology
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