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视频人脸的器官快速定位 被引量:1

Fast apparatus location in video face
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摘要 传统的人脸器官定位算法系统运算时间较长,不适于视频人脸的器官定位。运用了Adaboost从视频图像中检测出人脸区域并确定其位置,将人脸区域进行肤色分割并确定出器官位置:首先对视频相邻两帧的人脸肤色区域差分初步确定眼部区域,再根据人脸器官的几何分布特征精确的定位眼部区域。最后利用伪H分量的数据分布确定嘴唇区域。通过实验表明本文的视频人脸检测算法处理时间较短和定位准确率较高。 Traditional face apparatus location need more time to compute, it is not fit for apparatus location in video face. The authors use Adaboost algorithm to detect the face region from video images and get the position, divide the skin region from the face region and then do apparatus location as: first ,the authors can find the eye region by getting the difference of image from the two adjacent face skin regions, then the authors can confirm the exact eye region depending on the distribution character of the apparatus . At last, the authors use the distribution in pseudo hue level to divide the lip region from the face. Proven by the experiments, the method in this paper could detect the apparatus region quickly and precisely.
出处 《四川大学学报(自然科学版)》 CAS CSCD 北大核心 2009年第1期61-64,共4页 Journal of Sichuan University(Natural Science Edition)
基金 四川省青年软件创新工程(201)
关键词 视频人脸 器官定位 ADABOOST 伪色调分量 video face, apparatus location, adaboost, pseudo hue level
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  • 1顾华,苏光大,杜成.人脸的眼角自动定位[J].红外与激光工程,2004,33(4):375-379. 被引量:14
  • 2Brunelli R, Poggio T. Face recognition: Features versus templates. IEEE Transactions on Pattern Analysis and Machine Intelligence,1993,15(10):1042-1052.
  • 3Yang MH, Kriegman DJ, Ahuja N. Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002,24(1):34-58.
  • 4Bala J, DeJong K, Huang J, Vafaie H, Wechsler H. Visual routine for eye detection using hybrid genetic architectures. In: Backer E,Gelsema ES, eds. Proceedings of the 13th International Conference on Pattern Recognition. Los Alamitos: IEEE CS Press,1996,3:606-610.
  • 5Reinders MJT, Koch RWC, Gerbrands JJ. Locating facial features in image sequences using neural networks. In Essa I, ed.Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition Los Alamitos: IEEE CS Press, 1996.230--235.
  • 6Wu JX, Zhou ZH. Efficient face candidates selector for face detection. Pattern Recognition, 2003,36(5):1175-1186.
  • 7Kanade T. Picture processing by computer complex and recognition of human faces [Ph.D. Thesis]. Kyoto: Kyoto University, 1973.
  • 8Feng GC, Yuen PC. Variance projection function and its application to eye detection for human face recognition. Pattern Recognition Letters, 1998,19(9):899-906.
  • 9Feng GC, Yuen PC. Multi cues eye detection on gray intensity image. Pattern Recognition, 2001,34(5):1033-1046.
  • 10Alattar AM, Rajala SA. Facial features localization in front view head and shoulders images. In: Rodrignez J, ed. 1999 IEEE International Conference on Acoustics, Speech and Signal Processing (Icassp). Los Alamitos: IEEE CS Press, 1999,6:3557-3560.

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