Visual Tracking Algorithm Based on Feature Matching of Key Regions

YU Wang-sheng; TIAN Xiao-hua; HOU Zhi-qiang; HUANG An-qi; LIU Xiang

doi:10.3969/j.issn.0372-2112.2014.11.004

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Visual Tracking Algorithm Based on Feature Matching of Key Regions

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- Visual Tracking Algorithm Based on Feature Matching of Key Regions
- Acta Electronica Sinica Vol. 42, Issue 11, Pages: 2150-2156(2014)
- 作者机构：
  
  空军工程大学信息与导航学院,陕西,西安,710077
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61175029)
- DOI：10.3969/j.issn.0372-2112.2014.11.004
  CLC： TP391.41
- Published：2014
- 稿件说明：
移动端阅览
YU Wang-sheng, TIAN Xiao-hua, HOU Zhi-qiang, et al. Visual Tracking Algorithm Based on Feature Matching of Key Regions[J]. Acta Electronica Sinica, 2014, 42(11): 2150-2156.
DOI：

YU Wang-sheng, TIAN Xiao-hua, HOU Zhi-qiang, et al. Visual Tracking Algorithm Based on Feature Matching of Key Regions[J]. Acta Electronica Sinica, 2014, 42(11): 2150-2156. DOI： 10.3969/j.issn.0372-2112.2014.11.004.

摘要

针对视觉跟踪中目标表观的复杂变化问题

提出了一种基于关键区域特征匹配的鲁棒跟踪算法.首先对目标模板进行初始化并通过滤波预测得到目标候选;然后采用自适应标记分水岭算法对目标模板和目标候选进行分割以提取关键区域

并利用像素的空间和频率分布特性对关键区域进行多重特征描述;最后通过关键区域的特征匹配得到目标模板与目标候选的匹配关系

由此确定最终跟踪结果并进行模板更新.对目标发生尺度、遮挡、旋转、光照、姿态、复杂背景以及运动模糊等变化的视频序列进行了仿真测试.实验结果表明

所提算法能够有效处理目标表观的复杂变化问题

尤其对目标的部分遮挡、光照变化以及复杂背景等具有较强的鲁棒性.

Abstract

In order to cope with the complex variation of target appearance during visual tracking

a robust tracking algorithm based on feature matching of key regions is proposed.Firstly

it initializes the target model and obtains target candidate through filter prediction.Then

it extracts the key regions of target model and target candidate using adaptive marker-based watershed algorithm and describes them with multiple features.Finally

it matches the key regions to get the mapping from target model to target candidate and calculates the final tracking results to output and update the target model.The proposed algorithm is tested on the video database containing the appearance variation of scale

occlusion

rotation

illumination

pose

background clutters

and motion blur.The experimental results demonstrate that the proposed algorithm can well cope with the complex appearance variation

especially shows the robustness to the partial occlusion

illumination and background clutters.

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