Video dizilerinden çoğul biyometrik kimlik doğrulama = combining face and voice modalities for person verification from video sequences

In this paper, a multimodal person verification system is presented. The system is based on face and voice modalities. Fusion of information derived from each modality is performed at the matching swre level using sum rule. For face verification statistical subspace tools are utilized as feature exhactors. For speaker verification, me1 frequency cepstral coefficients are used as features and gaussian mixture models are used for modeling. Various wmbination cases are hied in the experiments and the results show that for each case the wmbined modalities performs betfer than the single modality