Recognizing Individual Sib in the Case of Siblings with Gait Biometric


W. Noorshahida Mohd-Isa, and Alam, Jahangir and Eswaran, Chikkanan and Junaidi Abdullah, (2011) Recognizing Individual Sib in the Case of Siblings with Gait Biometric. In: Informatics Engineering and Information Science. Communications in Computer and Information Science, 253 . Springer Berlin Heidelberg, pp. 112-122. ISBN Print ISBN: 978-3-642-25461-1, Online ISBN: 978-3-642-25462-8

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Gait is another potential human biometrics to look into whenever face recognition fails in video-based systems as is the case with siblings that have similar faces. We perform analyses on 10 pairs of siblings where their faces are assumed to have similarities. Our gait features are the angular displacement trajectories of walking individuals. We apply smoothing with the Bezier polynomial in our root-finding algorithm for accurate gait cycle extraction. Then, we apply classification using two different classifiers; the linear discriminant analysis (LDA) and the k-nearest neighbour (kNN). The best average correct classification rate (CCR) is 100% with a city-block distance kNN classifier. Hence, it is suggested that in the case where face recognition fails, gait may be the better alternative for biometric identification.

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 04 Nov 2013 06:01
Last Modified: 04 Nov 2013 06:01


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