Person Recognition using Multi-modal Biometrics - Face and Speech
Automated verification of human identity is indispensable in security and surveillance systems and also in applications involving assistive technology. Uni-modal systems relying on a single modality for authentication suffer from several limitations. Multi-modal systems consolidate evidence from multiple sources and are thus more reliable. The main objective of this project is to develop a robust recognition engine based on the face and speech modalities. Biometric authentication schemes based on audio and video modalities are non-intrusive and are therefore more suitable in real-world settings compared to the intrusive methods like fingerprint and retina scans. This is a collaborative project that brings in the expertise from two different fields - face based recognition (at ASU) and speech based recognition (at Tecnologico de Monterey, Mexico).