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车辆视频检测中自适应背景更新算法的研究与仿真实现

Research and Simulation on Adaptive Background Update Algorithm in Video Vehicle Detection
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摘要 本文主要对车辆视频检测中基于高斯混合模型的自适应背景更新算法进行了研究和仿真实现,并针对图像初始化的几种方法进行了研究和仿真。混合高斯模型算法可以较好地提取多模态图像中的背景与前景,统计直方图法则能较好地提取初始背景,实现背景更新。 This paper mainly researches and simulates the adaptive background update algorithm based on Gaussian Mixture Model （GMM） in video vehicle detection. Then, it researches on several methods of background initialization. According to GMM,it can be used to extract the background and foreground in multi-modal images. The statistical histogram method can extract the initial background and realize the background update perfectly.
作者 郭琳
机构地区 中国传媒大学广播电视数字化教育部工程研究中心
出处 《中国传媒大学学报（自然科学版）》 2013年第2期68-73,共6页 Journal of Communication University of China：Science and Technology
关键词 车辆视频检测 自适应背景更新 混合高斯模型 多帧平均法 统计直方图法 video vehicle detection adaptive background update Gaussian mixture model multi-frame av-erage method statistical histogram method
分类号 TN911.7 [电子电信—通信与信息系统]
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参考文献8

  • 1Friedman N, Russell S. Image segmentation in video sequences: a probabilistic approach. In: Proceedings of Thirteenth Conference on Uncer- tainty in Artificial Intelligence. Providence, Rhode Island, USA, Morgan Kaufmann Publish- ers, 1997,175 - 181.
  • 2Wren C R, Azarbayejani A, Darrell T, Pentland A P Pfinder. Real-time tracking of the human body [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997,19 (7) : 780 - 785.
  • 3Stauffer C, Grimson W. Adaptive background mixture models for real-time tracking [ J ]. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Fort Collins,Colorado, USA, IEEE, 1999,246 - 252.
  • 4李明之,马志强,单勇,张晓燕.复杂条件下高斯混合模型的自适应背景更新[J].计算机应用,2011,31(7):1831-1834. 被引量：15
  • 5LEE D S. Effective Gaussian mixture learning [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005,27 ( 5 ) : 827 - 832.
  • 6ZORAN Z. Recursive unsupervised learning of finite mixture models[ J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004,26(5) :651-656.
  • 7王齐.基于视频图像的交通监控系统研究[D].西安:西北工业大学,2005.
  • 8林洪文,涂丹,李国辉.基于统计背景模型的运动目标检测方法[J].计算机工程,2003,29(16):97-99. 被引量：80

二级参考文献15

  • 1STAUFFER C, GRIMSON W.Adaptive background mixture models for real-time tracking[C] // Proceedings of IEEE Conference on Vision and Pattern Collins. New York:IEEE, 1999:246-252.
  • 2LEE D S. Effective Gaussian mixture learning[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005,27(5): 827-832.
  • 3ZORAN Z. Recursive unsupervised learning of finite mixture models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(5): 651-656.
  • 4TOYAMA K, KUMM J, MEYERS B, et al. Wallflower: Principles and practive of background maintenance[C] // Proceedings of 1999 IEEE International Conference on Computer Vision. New York:IEEE, 1999:255-261.
  • 5Collins R, Lipton A,Kanade T,et al. A System for Video Surveillance and Monitoring.Tech. Report CM U-RI-TR-00-12,Robotics Institute,Carnegie Mellon University,2000-05.
  • 6Koller D, Daniilidis K,Nagel H.Model-bascd Object Tracking in Monocular Image Sequences of Road traffic Scenes.International Journal of Computer Vision, 1993,10(3).
  • 7Wren C R,Azarbayejani A,Darrell T.Plinder:Real_time Tracking of the Human Body.IEEE Transactions on Pattern Analysis and Machine Intelligence, 1977-07,7.
  • 8Haritaoglu I,Davis L S,Harwood D.W4 Who? When? Where? What? A Rreal Time System for Detecing and Tracking People.In FGR98,1998.
  • 9Mclvor M.Background Subtraction Techniques.IVCNZ00, Hamilton,New Zealand, 2000-11.
  • 10Toyama K,Krumm J.Brumitt B.et al.Wallowver; Principles and Practice of Background Maintenance.ln International Conference on Computer Vision (1999).

共引文献94

中国传媒大学学报（自然科学版）
2013年 第2期

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