Enhance ASM Based on DCT-SVM for Facial Feature Points Localization

摘要：

　　Focused on the facial feature points localization,the enhance ASM algorithm based on modeling texture by the DCT-SVM is proposed.First,the statistical shape model is built.Then,some key feature points are selected and their texture models are built by the DCT-SVM.In the subsequent searching,the feature points are divided into two classes based on their reliability gained by DCT-SVM detector,by combining the reliable feature points to the shape constraint,the original shape can finally match to the target face.Experiments show the algorithm is robust to the expressions change and can better locate the features than the traditional ASM.

关键词： Facial feature points localization active shape model (ASM) support vector machine(SVM) discrete cosine transform (DCT) least square method (LSM)

作者: Youjia Fu Jianwei Li Ruxi Xiang

作者单位: College of Computer Science & Engineering, Chongqing University of Technology,Chongqing 400054, Chin Key Laboratory of Opto-electronic Technology & System of the Ministry of Education,Chongqing Univers

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 820-824

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）