Face Recognition

This thesis presents a comprehensive overview of the problem of facial recognition. A survey of available facial detection algorithms as well as implementation and tests of different feature extraction and dimensionality reduction methods and light normalization methods are presented. A new feature extraction and identity matching algorithm, the Multiple Individual Discriminative Models (MIDM) algorithm, is proposed. MIDM is in collaboration with AAM-API, a C++ open source implementation of Active Appearance Models (AAM), implemented into the “FaceRec” Delphi 7 application, a real time automatic facial recognition system. AAM is used for face detection and MIDM for face recognition. Extensive testing of the MIDM algorithm is presented and its performance evaluated by the Lausanne protocol. The Lausanne protocol is a precise and widely accepted protocol for the testing of facial recognition algorithms. These test evaluations showed that the MIDM algorithm is superior to all other algorithms reported by the Lausanne protocol. Finally, this thesis presents a description of 3D facial reconstruction from a single 2D image. This is done by using prior knowledge in form of a statistical shape model of faces in 3D.