This paper presents an algorithm for measuring hair and face appearance in 2D images. Our approach starts by using learned mixture models of color and location information to sugg...
Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen,...
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
In this paper, a Bayesian method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constraints on image features as well as contextual relationships be...
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 sing...