吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (06): 1644-1649.doi: 10.7964/jdxbgxb201306034

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基于加权光流能量的异常行为检测

傅博1, 李文辉1,2, 陈博1, 王聪1,2, 王莹1,2   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012;
    2. 吉林大学 汽车仿真与控制国家重点实验室, 长春 130012
  • 收稿日期:2012-06-26 出版日期:2013-11-01 发布日期:2013-11-01
  • 通讯作者: 李文辉(1961-),男,教授,博士生导师.研究方向:计算机图形学.E-mail:liwh@jlu.edu.cn E-mail:liwh@jlu.edu.cn
  • 作者简介:傅博(1983-),男,博士研究生.研究方向:图像处理与模式识别.E-mail:fubocloud@163.com
  • 基金资助:

    国家自然科学基金项目(60873147,41001302).

Abnormal behavior detection based on weighted energy of optical flow

FU Bo1, LI Wen-hui1,2, CHEN Bo1, WANG Cong1,2, WANG Ying1,2   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130012, China
  • Received:2012-06-26 Online:2013-11-01 Published:2013-11-01

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摘要：

为了减少光线突变对光流提取的干扰,实时、可靠地提取运动目标前景,采用双背景模型方法,即自适应的滑动平均背景更新算法融合HSV颜色空间背景模型提取前景。在运动目标前景的最小邻接矩形区域内,采用Lucas-Kanade方法计算光流信息,通过光流信息计算出运动目标的单位加权光流能量来判断是否发生异常行为。在室内外环境的实验结果表明:该方法能够稳定地检测人的异常行为,鲁棒性较高,计算复杂度较低,能够满足实时性要求。

关键词: 计算机应用, 异常行为检测, 双背景建模, 单位光流

Abstract:

A human abnormal behavior detecting approach was proposed based on optical flow features in the motion area. An improved dual background model, which includes an adaptive running average background model and a HSV background model, was developed to indicate the variation of background pixels in order to increase the robustness against illustration change and environmental disturbance. The model can reliably extract the motion area. Foreground was obtained from video sequences by background subtraction. The motion area was labeled as several regions of interest, and the optical features in each labeled region were obtained using Lucas-Kanade algorithm. Amplitude based weighted unit energy derived from the optical flow features was defined to measure the anomaly of human activity. Experiments were conducted on various videos indoor and outdoor, and the results were presented to verify the effectiveness of the proposed scheme.

Key words: computer application, abnormal behavior detection, dual background modeling, unit optical flow energy

中图分类号: 

  • TP391

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