华南理工大学学报(自然科学版) ›› 2013, Vol. 41 ›› Issue (11): 23-29,35.doi: 10.3969/j.issn.1000-565X.2013.11.004

• 电子、通信与自动控制 • 上一篇    下一篇

基于排名的结构稀疏表示目标跟踪算法

侯跃恩1 李伟光1 四库2 曾顺星1 容爱琼1   

  1. 1.华南理工大学 机械与汽车工程学院,广东 广州 510640;2.东莞理工学院 机械工程学院,广东 东莞 523808
  • 收稿日期:2013-07-02 修回日期:2013-08-05 出版日期:2013-11-25 发布日期:2013-10-11
  • 通信作者: 侯跃恩(1983-),男,博士生,主要从事机器视觉和机器人控制研究. E-mail:houyueen@163.com
  • 作者简介:侯跃恩(1983-),男,博士生,主要从事机器视觉和机器人控制研究.
  • 基金资助:

    粤港关键领域重点突破项目(2011BZ100012);东莞市高等院校、 科研机构和医疗卫生单位科技计划重点项目(2011108101002)

Target Tracking Algorithm with Structured Sparse Representation Based on Ranks

Hou Yue- en1 Li Wei- guang1 Sekou Singare2 Zeng Shun- xing1 Rong Ai- qiong1   

  1. 1.School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China;2.College of Mechanical Engineering,Dongguan University of Technology,Dongguan 523808,Guangdong,China
  • Received:2013-07-02 Revised:2013-08-05 Online:2013-11-25 Published:2013-10-11
  • Contact: 侯跃恩(1983-),男,博士生,主要从事机器视觉和机器人控制研究. E-mail:houyueen@163.com
  • About author:侯跃恩(1983-),男,博士生,主要从事机器视觉和机器人控制研究.
  • Supported by:

    粤港关键领域重点突破项目(2011BZ100012);东莞市高等院校、 科研机构和医疗卫生单位科技计划重点项目(2011108101002)

摘要: 针对目前目标跟踪算法在复杂条件下跟踪效果差的问题,提出了基于排名的结构稀疏表示目标跟踪算法.该算法首先构造含有目标和背景信息的对象字典,用结构稀疏表示的方法线性表示候选目标,并将相关系数进行组合和排名.然后采用目标残差和背景残差相结合的方法计算各候选目标的残差得分,并进行排名.最后,通过稀疏系数和残差排名得到目标状态.试验证明,文中算法具有跟踪准确度高和鲁棒性强的特点.

关键词: 目标跟踪, 结构稀疏表示, 残差, 稀疏系数, 粒子滤波

Abstract:

As the existing tracking algorithms are of poor performance in complex situations,a target tracking algo-rithm with structured sparse representation is proposed based on ranks.In this algorithm,first,a target dictionarycontaining targets and background information is constructed.Next,the candidate targets are represented linearlyvia the structured sparse representation,and the corresponding correlation coefficients are combined and ranked.Then,the residual error scores of the candidate targets are computed by using the residual errors of the target andthe background,and the scores are ranked later,from which the target state is finally determined.Experimental re-sults show that the proposed tracking algorithm is of high tracking accuracy and strong robustness.

Key words: target tracking, structured sparse representation, residual error, sparse coefficient, particle filtering

中图分类号: