Multimodal person verification from video sequences

Abstract

In this paper, a multimodal person verification system based on fusing information derived from face speech signals is proposed. Principle component analysis and independent component analysis techniques are used for face verification and melfrequency-cepstral coefficients are used for speaker verification. The matching scores from individual modalities are combined using the sum rule. The results indicate that fusing indivual modalities improve overall performance of the verification system.