电信科学 ›› 2011, Vol. 27 ›› Issue (12): 81-84.doi: 10.3969/j.issn.1000-0801.2011.12.023

• 研究与开发 • 上一篇    下一篇

复杂监控环境下运动目标的检测和跟踪方法

关晓惠1,钱亚冠2,周志敏1   

  1. 1 浙江水利水电专科学校计算机与信息工程系 杭州 310018
    2 浙江科技学院理学院 杭州 310023
  • 出版日期:2011-12-15 发布日期:2011-12-15
  • 基金资助:
    浙江省教育厅科研资助项目

Object Detection and Tacking Algorithm in Intelligent Monitoring System

Xiaohui Guan1,Yaguan Qian2,Zhimin Zhou1   

  1. 1 Department of Computer and Information Engineering,Zhejiang Water Conservancy and Hydropower College, Hangzhou 310018, China
    2 Science College, Zhejiang University of Science and Technology, Hangzhou 310023, China
  • Online:2011-12-15 Published:2011-12-15

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摘要：

具有实时检测、跟踪和分析判断的智能化监控系统是智能化监控系统发展的必然趋势，本文提出一种在实时监控下检测和跟踪运动目标的方法，首先使用背景差分法检测出运动目标，并定期使用背景更新策略对参考背景进行局部更新，这样可以提高目标检测的精确度。目标跟踪时在不同的尺度空间获得目标的关键点，增强算法目标在遮挡情况下的鲁棒性，接下来使用 mean shift 算法估计目标在下一帧的位置。采用IBM 研究中心的测试视频序列对本文的方法进行了测试，实验结果表明，该方法是有效可行的。

关键词: 目标检测, 跟踪, 尺度空间, meanshift

Abstract:

Currently the intelligent monitoring system with real-time detection, tracking and analysis is the future trends. In this paper, we propose an algorithm to detect and track a moving object in real time surveillance environment. Firstly we adopt background difference method to detect the moving object.Then we use a local strategy to update changing background to adapt the complex environment,such as light variant,mutual transformation of foreground and background.In the tracking process,keypoints are obtained in different scale space to enhance the robustness of algorithm in object occlusion.Lastly mean shift method is used to estimate the position in next frame of object.The experiment result demonstrate s the feasibility and validity of our algorithm.

Key words: object detection, tracking, scale space, mean shift

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