Recent studies in patch-based Gaussian Mixture Model (GMM) approaches for face age estimation present promising results. We propose using a hidden Markov model (HMM) supervector t...
Xiaodan Zhuang, Xi Zhou, Mark Hasegawa-Johnson, Th...
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,...
In this paper, we introduce a Hybrid Hidden Markov Model (HMM) face recognition system. The proposed system contains a low-complexity 2-D HMM-based face recognition (LC 2D-HMM FR)...
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...
The spatial distribution of gray level intensities in an image can be naturally modeled using Markov Random Field (MRF) models. We develop and investigate the performance of face ...