CAJ | 학술논문

集成了基于肤色的人脸跟踪和基于PCA/BPNN(主成分分析/前馈神经网络)的人脸识别技术,提出了一种人脸实时跟踪与识别方法.该方法可以实现复杂背景下的人脸跟踪,并可处理人脸遮挡问题.通过平均视频序列中的多幅人脸图像,获得了很高的正确识别率.该方法在800 MHz主频的微机上实现,系统处理速度达20帧/s.
집성료기우부색적인검근종화기우PCA/BPNN(주성분분석/전궤신경망락)적인검식별기술,제출료일충인검실시근종여식별방법.해방법가이실현복잡배경하적인검근종,병가처리인검차당문제.통과평균시빈서렬중적다폭인검도상,획득료흔고적정학식별솔.해방법재800 MHz주빈적미궤상실현,계통처리속도체20정/s.
A framework of real-time face tracking and recognition is presented, which integrates skin-color-based tracking and PCA/BPNN (principle component analysis/back-propagation neural network) hybrid recognition techniques. The algorithm is able to track the human face against a complex background and also works well when temporary occlusion occurs. We also obtain a very high recognition rate by averaging a number of samples over a long image sequence. The proposed approach has been successfully tested by many experiments, and can operate at 20 frames/s on an 800 MHz PC.