Human Facial Feature Localisation by Gabor Filter and Clustering

摘要：

Human facial features localization is an important process of face recognition, since it helps generating face images in accordance with specified criteria, or building unique face model. This paper presents a novel method for finding facial features through Gabor filtering and k-means clustering analysis. By Gabor filtering, face images are transformed into magnitude responses. In magnitude responses, areas containing facial features demonstrate relatively strong responses. After thresholding magnitude responses, strong responses are remained, but weak responses are neglected. Points belonging to facial features are collected for the k-means clustering. Points are grouped into different clusters. Each cluster corresponds to a facial feature. By testing on the ORL face database, the method shows its accuracy and rapidness on locating facial features, such as eyes, nose, and mouth. It also displays its robustness on people who have thick beard or moustache.

作者: Mian Zhou Hong Wei Xiangjun Wang Pengcheng Wen Feng Liu

作者单位: State Key Laboratory of Precision Measuring Technology and Instruments,Tianjin University,Tianjin,Ch School of Systems Engineering,University of Reading,Reading,United Kingdom,RG6 6AY College of Precision Instrument and Opto-Electronics Engineering,Tianjin University,Tianjin,China,30

会议类型: 国际会议

会议名称: 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics(第二届智能人机系统与控制论国际学术会议 IHMSC 2010)

会议地点: 南京

会议语种:英文

页码: 353-356

在线出版日期: 2010-08-26（万方平台首次上网日期，不代表论文的发表时间）