Mean Shift tracking algorithm using joint histogram of colors and oriented gradients

被引：0

作者：

Dai, Shi-Jie ^{[1
]}

Qi, Jin-Yao ^{[1
]}

Yi, Dan ^{[1
]}

Shao, Meng ^{[1
]}

Li, Wei-Chao ^{[1
]}

机构：

[1] Research Institute of Robotics and Automation, Hebei University of Technology, Tianjin

来源：

Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2015年 / 23卷

关键词：

Illumination variation; Joint histogram; Mean Shift tracking; Object rotation; Object tracking; Partial occlusion;

D O I：

10.3788/OPE.20152313.0459

中图分类号：

学科分类号：

摘要：

The single orientation feature gets ineffective when tracking rotational object. For the sake of fulfilling object tracking in the scenes of illumination variation, rotation and partial occlusion, a joint histogram of colors and oriented gradients based Mean Shift tracking algorithm is presented. The joint histogram fuses the features of colors and oriented gradients by expanding the dimensions of the histogram. In this algorithm, IVF (illumination variation factor) is calculated by the model of illumination, which detects the degree of illumination variation. In the process of tracking, if IVF is below a certain threshold, color feature is taken as the principal feature so that the algorithm is robust to rotation, otherwise choose oriented gradients as principal feature for its robustness to illumination variation. The problem of partial occlusion can be figured out by dividing the object template into sub areas, and the position of object can be determined by the area that obtains largest similarity coefficient. The presented algorithm shows good performance in the experiments when dealing with complex scenes such as target rotation, illumination change and partial occlusion. © 2015, Chinese Academy of Sciences. All right reserved.

引用

页码：459 / 465

页数：6

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