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计算机工程

• 人工智能及识别技术 • 上一篇    下一篇

基于灰度触发的Mean Shift自动跟踪算法

喻旭勇,王直杰   

  1. (东华大学信息科学与技术学院,上海 201620)
  • 收稿日期:2012-12-06 出版日期:2014-01-15 发布日期:2014-01-13
  • 作者简介:喻旭勇(1987-),男,硕士研究生,主研方向:模式识别,图像处理;王直杰,教授、博士生导师
  • 基金资助:
    国家自然科学基金资助项目(61075105)

Mean Shift Automatic Tracking Algorithm Based on Gray Triggering

YU Xu-yong, WANG Zhi-jie   

  1. (College of Information Sciences and Technology, Donghua University, Shanghai 201620, China)
  • Received:2012-12-06 Online:2014-01-15 Published:2014-01-13

摘要: 为实现道路交通的车辆自动跟踪,提出一种基于灰度触发的Mean Shift自动跟踪算法。利用改进的高斯混合模型进行前景检测,有效抑制光照突变对于目标检测的影响,保证触发区域的灰度干扰降低到最少。设计基于虚拟区域灰度变化的触发方式,通过捕获虚拟触发区域内的灰度局部峰值,扩展目标搜寻区域进行运动车辆的锁定,进而实现核函数宽度自适应调整的Mean Shift跟踪。实验结果表明,该方法能准确实现自动触发跟踪,触发精度较高,具有较好的实用价值。

关键词: 运动目标检测与跟踪, 混合高斯模型, 灰度触发, Mean Shift算法

Abstract: In order to achieve the automatic tracking of vehicles in road traffic, this paper proposes a mean shift tracking algorithm based on gray triggering. It detects the targets using a modified Gaussian mixture model to reduce the influences of the target detection caused by sudden changes of light. Thereby it guarantees the minimum gray interference on triggered areas. This algorithm designs a trigger method based on changes of the gray degree in virtual region. By capturing the local peak gray value in the triggered area, this method expends target search area to lock the moving vehicles and thereby achieves the Mean Shift tracking in which the kernel function adjusts its width automatically. Experimental result shows that this method achieves automatic trigger tracking efficiently and accurately, has high trigger accuracy and good practical value.

Key words: movement target detection and tracking, mixture Gaussian model, gray triggering, Mean Shift algorithm

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