Electronic Science and Technology ›› 2019, Vol. 32 ›› Issue (9): 32-37.doi: 10.16180/j.cnki.issn1007-7820.2019.09.007

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Multi-face Tracking and Optimal Face Extraction

TIAN Xiong,WU Wei,LIU Xiaoshang,WU Xiu   

  1. School of Electronic Information,Hangzhou Dianzi University,Hangzhou 310018,China
  • Received:2018-09-07 Online:2019-09-15 Published:2019-09-19
  • Supported by:
    National Natural Science Foundation of China International (Regional) Cooperation and Exchange Project(61411136003)

Abstract: Aim

ing at the problem that repeated recognition of the same person in video face recognition system, a multi-face tracking and optimal face extraction method was proposed. Using ViBe modeling to extract the motion area, reducing the data processing area; The Haar feature was combined with the AdaBoost algorithm to detect the face, and the skin color detection was used to determine whether there was a false detection; Tracking faces with CamShift algorithm; Using the Sobel operator to got a clearer face image. Experiments showed that under this method, the face false detection rate was reduced from 2.8% to 0.2%. For 100 frames, the average processing time was reduced from 112 milliseconds per frame to 45.6 milliseconds, and the processing speed was significantly improved.

Key words: face detection, face tracking, AdaBoost, Haar, CamShift, Sobel

CLC Number: 

  • TP391.41