• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 论文 • 上一篇    下一篇

基于外观模型的目标跟踪算法研究进展

李娜1,2,3,赵祥模1,赵凤2,3,刘卫华2,3,王倩2,3   

  1. (1.长安大学信息工程学院,陕西 西安710064;2.西安邮电大学通信与信息工程学院,陕西 西安 710121;
    3.电子信息现场勘验应用技术公安部重点实验室,陕西 西安 710121)
  • 收稿日期:2015-11-20 修回日期:2016-01-22 出版日期:2017-03-25 发布日期:2017-03-25
  • 基金资助:

    国家自然科学基金(61102095);公安部科技强警基础工作专项(2015GABJC51);陕西省国际合作项目(2015KW-014);陕西省教育厅基础专项(15JK1661,15JK1660);陕西省碑林区科技项目(GX1502)

Object tracking algorithms based on
appearance models:A survey

LI Na1,2,3,ZHAO Xiang-mo1,ZHAO Feng2,3,LIU Wei-hua2,3,WANG qian2,3   

  1. (1.School of Information Engineering,Chang’an University,Xi’an 710064;
    2.School of Communication and Information Engineering,Xi’an University of Posts and Telecommunications,Xi’an 710121;
    3.Key Laboratory of Electronic Information Application Technology
    for Scene Investigation,Ministry of Public Security,Xi’an 710121,China)
  • Received:2015-11-20 Revised:2016-01-22 Online:2017-03-25 Published:2017-03-25

摘要:

基于视觉的目标跟踪是模式识别、计算机视觉、机器学习等多个学科的交叉研究课题,在视频监控、视频压缩编码、视频检索、智能交通等领域有着十分广泛的应用。为了使国内外同行对基于外观模型的目标跟踪方法有一个较为全面的了解,对其进行了系统总结。在介绍跟踪算法原理的基础上,重点阐述了两大类基于外观模型的目标跟踪方法:产生式方法和判别式方法,深入讨论了其中的典型算法和研究成果,并对这些算法在公开数据集上的测试结果进行了分析比较,最后展望了该领域未来的发展方向。
 

关键词: 目标跟踪, 外观模型, 产生式方法, 判别式方法

Abstract:

Visual object tracking is a hot topic in areas of pattern recognition, computer vision and machine learning, which has a wide range of applications in video surveillance, video compressing coding, video retrieval, intelligent transport system and so on. In order to make a better understanding of object tracking algorithms based on appearance models for domestic and international peers, we comprehensively review the latest research progress in this field. We firstly introduce the mechanism of tracking algorithms.Then we summarize current researches on visual object tracking based on appearance models, including generative and discriminative methods. Thirdly, the state-of-the-art tracking algorithms are compared on the public datasets. We finally discuss future research trend of object tracking.

Key words: object tracking, appearance model, generative methods, discriminative methods