Face Recognition using survival exponential entropy Based on Markov Random Field Modeling
In this paper, a new method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constrains on image features as well as contextual relationships between them are explored and encoded into a cost function derived based on a statistical model of MRF. The face images are divided into salient regions, and the MRF model is used to represent the relationship between the regions and region IDS. We use a new salient region detector based on the survival exponential entropy (SEF), the survival exponential entropy based normalized mutual information is proposed and integrated with the MRF model as the similarity measure to reflect the similarity between two facial images. The proposed method is evaluated and compared with several stateof-the-art face recognition methods, experiments demonstrate promising results.
Face Recognition Markov random field(MRF) survival exponential entropy (SEE)
BAO Jin XIE Mei
School of Electronic Engineering University of Electronic Science and Technology of China Chengdu, Sichuan, China
国际会议
贵阳
英文
202-205
2011-01-26（万方平台首次上网日期，不代表论文的发表时间）