基于视频的人脸检测算法研究

doi:10.16180/j.cnki.issn1007-7820.2020.02.005

Abstract

Abstract:

Aiming at the shortcomings of the traditional AdaBoost algorithm in detecting high false detection rate in video, an improved face detection algorithm combining motion analysis and skin color detection was proposed. The proposed method extracted motion prospects through motion detection, and selected the skin color model to obtain the similarity of the face skin color, and further narrowed the detection range by using the geometric features. The face candidate region was detected in real time detection the improved AdaBoost algorithm which was added with new Haarfeatures and improved weight update mode.The experimental results showed that compared with the traditional AdaBoost method and the AdaBoost method with skin color detection, the false detection rate of this method was reduced by 18.68% and 8.79% respectively, and the detection time was shortened by about 800 ms and 250 ms, respectively.

Key words: face detection, motion analysis, skin color model, AdaBoost algorithm, Haar feature, weight update

CLC Number:

TP391.41

WANG Xin,WU Wei,ZENG Zhao. Research on Face Detection Algorithm Based on Video[J].Electronic Science and Technology, 2020, 33(2): 25-31.

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References 15

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检测算法	实际人脸个数	检测人脸数	正检人脸数	错检人脸数	漏检率/%	误检率/%
传统AdaBoost	204	253	202	51	0.98	20.15
改进AdaBoost	204	224	201	23	1.47	10.26
本文算法	204	203	200	3	1.96	1.47

检测算法	视频格式
检测算法	1 280×1 080	1 280×960
传统的AdaBoost	983	805
改进的AdaBoost	358	312
本文算法	92	86

Research on Face Detection Algorithm Based on Video

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