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Person Identity Verification Based on Multimodal Face-Gait Fusion


Emdad Hossain, Girija Chetty


Vol. 11  No. 6  pp. 77-86


In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity.


Biometrics, gait recognition, PCA, LDA, Eigenface, Fisherface, Multivariate Gaussian Classifier