A Novel Markov Random Field Based Deformable Model for Face Recognition

In this paper, a new scheme to address the face recognition problem is proposed. Different from traditional face recognition approaches which represent each facial image by a single feature vector as the classification problem, the proposed method establishes a new way to formulate the face recognition problem as a deformable image registration problem. The main contributions of the paper lie in the following aspects: (i) Each pixel is represented by an anatomical feature signature calculated from its corresponding best scale salient region by using a new salient region detector based on the survival exponential entropy (SEE); (ii) The face recognition problem is formulated as a deformable image registration problem, the deformation model is represented by a Markov random field (MRF) labeling framework. Explicit pixel correspondence is established by the deformation framework. (iii) The survival exponential entropy based normalized mutual information (SEE-NMI) is proposed and integr...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Shu Liao, Albert C.S. Chung
• Keywords: Computer Vision, CVPR 2010, Face Recognition, Face Recognition Approaches, Face Recognition Problem