文献类型：期刊文献

英文题名：Robust Realtime Face Recognition And Tracking System

作者：Chen, Kai[1];Zhao, Le Jun[1]

机构：[1]East China Univ Sci & Technol, Beijing, Peoples R China

年份：2009

卷号：9

期号：2

起止页码：82

外文期刊名：JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY

收录：WOS:【ESCI(收录号:WOS:000421702700006)】；

语种：英文

外文关键词：meanshift; Kalman filter; svm; wavelet; Realtime face detection; Realtime face tracking; face recognition

摘要：There's some very important meaning in the study of realtime face recognition and tracking system for the video monitoring and artifical vision. The current method is still very susceptible to the illumination condition, non-real time and very common to fail to track the target face especially when partly covered or moving fast. In this paper, we propose to use Boosted Cascade combined with skin model for face detection and then in order to recognize the candidate faces, they will be analyzed by the hybrid Wavelet, PCA(principle component analysis) and SVM(support vector machine) method. After that, Meanshift and Kalman filter will be invoked to track the face. The experimental results show that the algorithm has quite good performance in terms of real-time and accuracy.