Title :
A novel Bayesian shape model for facial feature extraction
Author :
Zhong Xue ; Li, Stan Z. ; Dinggang Shen ; Eam Khwang Teoh
Author_Institution :
Pennsylvania Univ., Philadelphia, PA, USA
Abstract :
This paper presents a novel application of the Bayesian shape model (BSM) for facial feature extraction. First, a full-face model is designed to describe the shape of a face, and the PCA is used to estimate the shape variance of the face model. Then, the BSM is applied to match and extract the face patch from input face images. Finally, using the face model, the extracted face patches are easily warped or normalized to a standard view. Applications of this facial feature extraction algorithm include face recognition, face video coding and retrieval, face animation and multimedia.
Keywords :
belief networks; face recognition; feature extraction; Bayesian shape model; face animation; face images; face patch; face recognition; face video coding; face video retrieval; facial feature extraction; facial shape; full-face model; multimedia; shape variance estimation; warping; Active contours; Bayesian methods; Facial features; Nose; Principal component analysis; Prototypes; Shape;
Conference_Titel :
Control, Automation, Robotics and Vision, 2002. ICARCV 2002. 7th International Conference on
Print_ISBN :
981-04-8364-3
DOI :
10.1109/ICARCV.2002.1234878