Probabilistic recognition of human faces from video
Computer Vision and Image Understanding - Special issue on Face recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Locating and extracting the eye in human face images
Pattern Recognition
A Bayesian approach to audio-visual speaker identification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Human Lips as Emerging Biometrics Modality
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Lips Recognition for Biometrics
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Dynamic visual features for audio-visual speaker verification
Computer Speech and Language
Intelligent computing for automated biometrics, criminal and forensic applications
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Combining dynamic texture and structural features for speaker identification
Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence
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As the low-cost video transmission becomes popular, video based bimodal (audio and visual) authentication has great potential in various applications that require access control. It is especially useful for hand-held terminals, which are often used under adverse environments, where the signal quality is rather poor. When human voice is used for authentication, one of the most relevant visual features is the dynamic movement of lips. In this research, we investigate on the use of static and dynamic features of speaking lips in the context of voice based authentication. A new feature representation that preserves both appearance and motion pattern of speaking lips is proposed. The dimension of extracted features is reduced by multiple discriminant analysis (MDA) and the method of nearest neighbor is used for classification. Our method can achieve an identification rate of 98% with only lips features for 200 clients of the XM2VTS database. Experiments on speaker verification using fused audio and visual features are on-going.