• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2010, Vol. 32 ›› Issue (6): 118-121.doi: 10.3969/j.issn.1007130X.2010.

• 论文 • 上一篇    下一篇

智能视频监控系统中物体遗留检测方法的研究

孔英会,张新新,王蕴珠   

  1. (华北电力大学电气与电子工程学院,河北 保定 071003)
  • 收稿日期:2009-09-15 修回日期:2009-12-17 出版日期:2010-06-01 发布日期:2010-06-01
  • 通讯作者: 张新新 E-mail:xinxin2882@126.com
  • 作者简介:孔英会(1964),女,河北冀县人,博士,教授,研究方向为智能信息处理和视频分析;张新新,硕士生,研究方向为智能信息处理和视频分析。

Research on the Detection of the Objects Left Behind in Intelligent Video Surveillance Systems

KONG Yinghui,ZHANG Xinxin,WANG Yunzhu   

  1. (School of Electrical and Electronics Engineering,North China Electric Power University,Baoding 071003,China)
  • Received:2009-09-15 Revised:2009-12-17 Online:2010-06-01 Published:2010-06-01

摘要:

本文针对智能视频监控中的物体遗留事件检测进行了研究,给出了一套完整的检测方案。多高斯模型用于运动目标检测,其自适应性很好地解决了背景帧不断变化所带来的影响;MeanShift算法用于运动目标的跟踪,使得监控对象不再限于固定区域;目标的七阶不变矩可以很好地描述目标特征,利用这一特征通过支持向量机对目标进行识别。实验结果证明了本文方法的有效性。

关键词: 智能视频监控, 多高斯模型, MeanShift跟踪算法, 支持向量机, 七阶不变矩

Abstract:

The paper studies the detection of the event of the objects left behind in intelligent video surveillance systems,and gives a complete set of test schema. The multipleGaussian model is used for the detection of the moving objects,and its adaptability well solve the impact of changing background frame.The  MeanShift algorithm is used for tracking the moving targets,which expands the scope,not only limited scope.The feature of Sevenband Moment Invariants well describe the target, through which support Vector Machine can identify the objects. The experimental results prove the effectiveness of the method.

Key words: intelligent video surveillance;multiple Gaussian model;MeanShift tracking

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