Abstract
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.
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Mohd-Isa, W.N., Abdullah, J., Alam, J., Eswaran, C. (2011). Recognizing Individual Sib in the Case of Siblings with Gait Biometric. In: Abd Manaf, A., Sahibuddin, S., Ahmad, R., Mohd Daud, S., El-Qawasmeh, E. (eds) Informatics Engineering and Information Science. ICIEIS 2011. Communications in Computer and Information Science, vol 253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25462-8_10
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DOI: https://doi.org/10.1007/978-3-642-25462-8_10
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