Towards building a Practical Face Recognition System
نویسندگان
چکیده
This thesis analyzes the various modeling techniques for face recognition that are available to us within the eigenface framework and experiments with different methods that can be used to match faces using eigenfaces. It presents a probabilistic approach to matching faces and demonstrates it's superiority over other methods. It also carries out comprehensive parameter exploration experiments that determine the optimal parameter values for recognition. Finally it lays down some foundation for future work for improvement in face detection wherein a similar Baysian framework can be implemented for detection. Thesis Supervisor: Alex P. Pentland Title: Toshiba Professor, Media Arts and Sciences
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