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Distance-driven fusion of gait and face for human identification in video

Geng, Xin, Wang, Liang, Li, Ming, Wu, Qiang and Smith-Miles, Kate 2007, Distance-driven fusion of gait and face for human identification in video, in IVCNZ 2007 : Proceedings of Image and Vision Computing New Zealand, Image and Vision Computing NZ, [Hamilton, N.Z.], pp. 19-24.

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Title Distance-driven 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 Image and Vision Computing New Zealand. Conference (2007: Hamilton, N.Z.)
Conference location Hamilton, New Zealand
Conference dates 5-7 December 2007
Title of proceedings IVCNZ 2007 : Proceedings of Image and Vision Computing New Zealand
Editor(s) Cree, Michael J.
Publication date 2007
Conference series Image and Vision Computing New Zealand Conference
Start page 19
End page 24
Publisher Image and Vision Computing NZ
Place of publication [Hamilton, N.Z.]
Keyword(s) human identification
multi-biometric fusion
face
gait
computer vision
Summary Gait and face are two important biometrics for human identification. Complementary properties of these two biometrics suggest fusion of them. The relationship between gait and face in the fusion is affected by the subject-to-camera distance. On the one hand, gait is a suitable biometric trait for human recognition at a distance. On the other hand, face recognition is more reliable when the subject is close to the camera. This paper proposes an adaptive fusion method called distance-driven fusion to combine gait and face for human identification in video. Rather than predefined fixed fusion rules, distance-driven fusion dynamically adjusts its rule according to the subject-to-camera distance in real time. Experimental results show that distance-driven fusion performs better than not only single biometric, but also the conventional
static fusion rules including MEAN, PRODUCT, MIN, and MAX.
Notes Reproduced with the specific permission of the copyright owner.
ISBN 9780473130084
0473130084
Language eng
Field of Research 080104 Computer Vision
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2007, Image and Vision Computing NZ
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008095

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