计算机科学 ›› 2012, Vol. 39 ›› Issue (12): 16-24.

• 综述 • 上一篇    下一篇

基于Mean Shift的视觉目标跟踪算法综述

顾幸方,茅耀斌,李秋洁   

  1. (南京理工大学自动化学院 南京210094)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Survey on Visual Tracking Algorithms Based on Mean Shift

  • Online:2018-11-16 Published:2018-11-16

摘要: 基于Mean Shift的视觉跟踪算法具有计算复杂度低、调节参数少、稳健性较好和易于工程实现等优点,是目前视觉跟踪领域的重要研究方向。首先介绍了经典的Mean Shift跟踪算法,分析了此跟踪框架存在的缺陷。然后从目标模型表达、模型更新、尺度与方向佑计、抗遮挡跟踪和快速目标跟踪等J个方面详细地综述了Mean Shift跟踪算法的发展与改进。针对上述每个方面,对典型方法与最近研究成果进行了介绍与评述。最后展望了Mean Shift跟踪今后的研究方向与发展趋势。

关键词: 视觉跟踪,均值漂移,目标模型

Abstract: Mean-shift based visual tracking algorithms have several desirable properties, such as computational efficiency,few tuning parameters, relatively high robustness in performance and straightforward implementation, which make them to become an appealing topic in visual tracking research area. Firstly, original mean shift tracking algorithm was introduced and its defects were pointed out afterwards. hhen improvements of the original algorithm were elaborately discussed from five aspects, namely generative and discriminative object appearance model, model update mechanism,scale and orientation adaptation, anti-occlusion and fast moving object tracking. Both classical algorithms and recent advances are included in each aspect. Finally,the prospects of mean-shift based tracking were presented.

Key words: Visual tracking, Mean shift, Object appearance model

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