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.
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.
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Field of Research
080109 Pattern Recognition and Data Mining
Socio Economic Objective
970108 Expanding Knowledge in the Information and Computing Sciences
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