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Information Fusion For Identity Verification
2011
Zenodo
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
doi:10.5281/zenodo.1077900
fatcat:rqzohllvhfgbfk5muko3v6lazi