NDLI: Automatic Gait Recognition Using Weighted Binary Pattern on Video

Content Provider	IEEE Xplore Digital Library
Author	Kusakunniran, W. Qiang Wu Hongdong Li Jian Zhang
Copyright Year	2009
Abstract	Human identification by recognizing the spontaneous gait recorded in real-world setting is a tough and not yet fully resolved problem in biometrics research. Several issues have contributed to the difficulties of this task. They include various poses, different clothes, moderate to large changes of normal walking manner due to carrying diverse goods when walking, and the uncertainty of the environments where the people are walking. In order to achieve a better gait recognition, this paper proposes a new method based on Weighted Binary Pattern (WBP). WBP first constructs binary pattern from a sequence of aligned silhouettes. Then, adaptive weighting technique is applied to discriminate significances of the bits in gait signatures. Being compared with most of existing methods in the literatures, this method can better deal with gait frequency, local spatial-temporal human pose features, and global body shape statistics. The proposed method is validated on several well known benchmark databases. The extensive and encouraging experimental results show that the proposed algorithm achieves high accuracy, but with low complexity and computational time.
Starting Page	49
Ending Page	54
File Size	355413
Page Count	6
File Format	PDF
ISBN	9781424447558
DOI	10.1109/AVSS.2009.44
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-02
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Biometrics Deformable models Shape Biological system modeling Face recognition local binary pattern Humans Kinematics Frequency Pattern recognition Gait recognition
Content Type	Text
Resource Type	Article

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