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Adaptive fusion of gait and face for human identification in video

Geng, Xin, Wang, Liang, Li, Ming, Wu, Qiang and Smith-Miles, Kate 2008, Adaptive fusion of gait and face for human identification in video, in WACV 2008 : Proceedings of the IEEE 2008 Workshop on Application of Computer Vision, IEEE, Piscataway, N.J., pp. 1-6.

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Title Adaptive fusion of gait and face for human identification in video
Author(s) Geng, Xin
Wang, Liang
Li, Ming
Wu, Qiang
Smith-Miles, Kate
Conference name IEEE Workshop on Application of Computer Vision (2008 : Colorado Springs, Colo.)
Conference location Colorado Springs, Colo.
Conference dates 7-9 January 2008
Title of proceedings WACV 2008 : Proceedings of the IEEE 2008 Workshop on Application of Computer Vision
Editor(s) [Unknown]
Publication date 2008
Conference series IEEE Workshop on Application of Computer Vision
Start page 1
End page 6
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Summary Most work on multi-biometric fusion is based on static fusion rules which cannot respond to the changes of the environment and the individual users. This paper proposes adaptive multi-biometric fusion, which dynamically adjusts the fusion rules to suit the real-time external conditions. As a typical example, the adaptive fusion of gait and face in video is studied. Two factors that may affect the relationship between gait and face in the fusion are considered, i.e., the view angle and the subject-to-camera distance. Together they determine the way gait and face are fused at an arbitrary time. Experimental results show that the adaptive fusion performs significantly better than not only single biometric traits, but also those widely adopted static fusion rules including SUM, PRODUCT, MIN, and MAX.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 9781424419135
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2008, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018141

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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