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智能视频监控中异常行为识别研究 被引量：12

Research on Abnormal Behavior Recognition in Intelligent Surveillance
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摘要 通过对HSV空间阴影检测与RGB空间阴影检测进行比较,分析了两种方法对消除阴影的效果,得出采用RGB空间阴影检测方法消除阴影对运动目标的识别更为准确.通过给出人的异常行为判别准则来识别运动目标是否属于消失、攀爬、跌倒等情况,实验结果表明该识别方法简单、快速、准确,取得了较好的识别效果. This paper first compares HSV space for shadow detection and RGB space for shadow detection and analyze the effect on eliminating the shadow. The author concludes that RGB space for shadow detection is more suitable for detection of moving targets. What＇s more,in this paper,a couple of criterions are defined to analyze whether people disappear,climb,or fall. Experiments demonstrate that the approach which is proposed on abnormal behavior recognition is easy,fast and effective and achieves good recognition effect.
作者 陈颖鸣 陈树越 张显亭
机构地区 中北大学信息与通信工程学院 中北大学仪器科学与动态测试教育部重点实验室
出处 《微电子学与计算机》 CSCD 北大核心 2010年第11期102-105,共4页 Microelectronics & Computer
关键词 HSV彩色空间 RGB彩色模型 阴影消除 智能监控 异常行为 HSV color space RGB color model shadow removal intelligent surveillance abnormal behavior
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献7

  • 1Li Yun, Xu Chunjing, Liu Jianzhuang, et al. Detecting irregularity in videos using kernel estimation and KID trees [C]// Proceedings of the 14th annual ACM international conference on Multimedia. New York: ACM Press, 2006: 639 - 642.
  • 2Wu X Y, Ou Y S, Qianhh, et al. A detection system for human abnormal behavior[C]// IEEE International Conference on Intelligent Robots and Systems. University of Maryland, 2005 : 1204 - 1208.
  • 3张哲源,史颖欢,高阳.基于色彩和形态特征的人阴影检测方法[J].微电子学与计算机,2009,26(10):86-88. 被引量：3
  • 4Cucchiara R, Grana C, Piccardi M, et al. Improving shadow suppression in moving object detection with HSV color information[C]//Proceedings of IEEE Intelligent Transportation System Conference ( ITSC 2001). Oakland, CA, USA, 2001:334 - 339.
  • 5Song Xuehua, Ding Yan, Gen Jianfeng, et al. Shadow removal of vehicles in a video system based on RGB chroma model[ C ]//2008 International Conference on Computer Science and Software Engineering. China: Hongkong, 2008,1160:977- 980.
  • 6Joo S, Zheng Q. A temporal variance- based moving target detector[M]. Berlin: Springer, 2005.
  • 7陈柏生,陈锻生.基于归一化rgb彩色模型的运动阴影检测[J].计算机应用,2006,26(8):1879-1881. 被引量：15

二级参考文献14

  • 1Haritaoglu I, Harwood D, Davis L S. W4: real- time surveillance of people and their activities[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2000,22(8) :809 - 830.
  • 2Prati A, Mimic I, Trivedi M, et al. Detecting moving shadows: algorithms and evaluation [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(7) :918- 923.
  • 3Horprasert T, Harwood D, Davis L S. A statistical approach for real - time robust background subtraction and shadow detection[ C]//IEEE ICCV' 99 FRAMERATE Workshop. Canada: University of Toronto, 1999.
  • 4Mikic I, Cosman P, Kogut G, et al. Moving shadow and object .detection in traffic scenes[C]//ICPR. Spain, 2000.
  • 5Nadimi S, Bhanu B. Physical models for moving shadow and object detection in video [J ]. IEEE Transaction on Pattern Analysis And Machine Intelligence, 2004,26 (8) : 1079 - 1087.
  • 6Remagnino P, Jones G A, Paragios N, et al. Video- based surveillance systems: computer vision and distributed processing[ M]. Massachusetts: Kluwer Aeademic Publishers, 2001.
  • 7Stauder J, Mech R, Ostermann J. Detection of moving cast shadows for obiect segmentation[J]. IEEE Transactions on Multimedia, 1999,1 (1) : 65 - 76.
  • 8Fung G S K, Yung N H C, Pang G K H. Towards detection of moving cast shadows for visual traffic surveillance [ C]//IEEE International Conference on Systems, Man and Cybernetics. USA, Tucson, 2001.
  • 9WANG C,HUANG L,ROSENFELD A.Detecting clouds and cloud shadows on aerial photographs[J].Pattern Recognition Letters,1991,12(1):55-64.
  • 10YONEYAMA A,YEH CH,KUO C-C J.Moving cast shadow elimination for robust vehicle extraction based on 2D joint vehicle/shadow models[A].Proceedings of IEEE Conference on Advanced Video and Signal Based Surveillance[C].Los Angeles,2003.229-236.

共引文献16

同被引文献71

引证文献12

二级引证文献48

微电子学与计算机
2010年 第11期

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