Multimodal Face-Gait Fusion for Biometric Person Authentication

In this paper we propose a novel multimodal fusion 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 when fused in either hierarchical or holistic fusion, can lead to powerful identity verification that can capture the inherent multimodality in walking gait patterns and ascertain the identity from low resolution surveillance videos.