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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Multimodal Identity Verification Based on Learning Face and Gait Cues
verfasst von : Emdad Hossain, Girija Chetty
Erschienen in: Neural Information Processing
Verlag: Springer Berlin Heidelberg
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In this paper we propose a novel multimodal Bayesian approach based on PCA-LDA processing for person identification from low resolution surveillance video with cues extracted from gait and face biometrics. The experimental evaluation of the proposed scheme on a publicly available database [2] showed that the combined PCA-LDA face and gait features can lead to powerful identity verification and can capture the inherent multimodality in walking gait patterns and discriminate the identity from low resolution surveillance videos.