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An improved Vibe algorithm for illumination mutations 被引量:2

一种面向光照突变的改进Vibe算法
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摘要 The visual background extractor(Vibe)algorithm can lead to a large area of false detection in the extracted foreground target when the illumination is mutated.An improved Vibe method based on the YCbCr color space and improved three-frame difference is proposed in this paper.The algorithm detects the illumination mutation frames accurately based on the difference between the luminance components of two frames adjacent to a video frame.If there exists a foreground moving target in the previous frame of the mutated frame,three-frame difference method is utilized;otherwise,Vibe method using current frame is used to initialize background.Improved three-frame differential method based on the difference in brightness between two frames of the video changes the size of the threshold adaptively to reduce the interference of noise on the foreground extraction.Experiment results show that the improved Vibe algorithm can not only suppress the“ghost”phenomenon effectively but also improve the accuracy and completeness of target detection,as well as reduce error rate of detection when the illumination is mutated.
作者 LIANG Jincheng WANG Xiaopeng WANG Qingsheng 梁金诚;王小鹏;王庆圣(兰州交通大学电子与信息工程学院,甘肃兰州730070)
出处 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2022年第2期184-191,共8页 测试科学与仪器(英文版)
基金 National Natural Science Foundation of China(No.61761027)。
关键词 moving target detection visual background extractor(Vibe)algorithm YCbCr color space three-frame difference method 运动目标检测 Vibe算法 YCbCr彩色空间 三帧差分法
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  • 1陈俊超,张俊豪,刘诗佳,陆小锋.基于背景建模与帧间差分的目标检测改进算法[J].计算机工程,2011,37(S1):171-173. 被引量:23
  • 2WREN C R, AZARBAYEJANI A, DARRELL T, et al. Pfinder: Real-time tracking of the human body [ J ]. Pat- tern Analysis and Machine Intelligence, IEEE Transac- tions on, 1997, 19(7) : 780-785.
  • 3HARITAOGLU I, HARWOOD D, DAVIS L S. W 4 S: A real-time system for detecting and tracking people in 2 1/2DIM]. Computer Vision-ECCV98. Springer Berlin Heidelberg, 1998 : 877-892.
  • 4ZIVKOVIC Z. Improved adaptive Gaussian mixture model for background subtraction [ C ]. Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on. IEEE, 2004, 2: 28-31.
  • 5KIM K, CHALIDABHONGSE T H, HARWOOD D, et al. Real-time foreground - background segmenta- tion using codebook model [ J]. Real-time Imaging, 2005, 11(3): 172-185.
  • 6GODBEHERE A B, MATSUKAWA A, GOLDBERG K. Visual tracking of human visitors under variable- lighting conditions for a responsive audio art installation [ C ]. American Control Conference ( ACC ), IEEE, 2012: 4305-4312.
  • 7BARNICH O, VAN DROOGENBROECK M. Vibe. A universal background subtraction algorithm for video se- quences [ J ]. Image Processing, IEEE Transactions on, 2011, 20(6) : 1709-1724.
  • 8VAN DROOGENBROECK M, PAQUOT O. Background subtraction: experiments and improvements for Vibe [ C ]. Computer Vision and Pattern Recognition Workshops ( CVPRW), 2012 IEEE Computer Society Conference on IEEE, 2012: 32-37.
  • 9SANIN A, SANDERSON C, LOVELL B C. Improved shadow removal for robust person tracking in surveillance scenarios[ C]. Pattern Recognition (ICPR), 2010 20th International Conference on IEEE, 2010: 141-144.
  • 10CUCCHIARA R, GRANA C, PICCARDI M, et al. Detecting objects, shadows and ghosts in video streams by exploiting color and motion information [ C ]. Image Analysis and Processing, 2001. Proceedings. llth International Conference on IEEE, 2001 : 360-365.

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