Multi-scale mean shift tracking

作者：Yu, Wangsheng^*; Tian, Xiaohua; Hou, Zhiqiang; Zha, Yufei; Yang, Yuan

来源：IET Computer Vision, 2015, 9(1): 110-123.

DOI：10.1049/iet-cvi.2014.0077

• image sequences
• object tracking
• iterative methods
• multiscale mean shift tracking algorithm
• background weighted spatial histogram
• three-dimensional mean shift tracking algorithm
• target template
• three-dimensional spatial histogram
• three-dimensional mean shift iteration
• two-dimensional image plane scale estimation
• background information
• target candidate model
• similarity measure
• complex appearance variations

In this study, a three-dimensional mean shift tracking algorithm, which combines the multi-scale model and background weighted spatial histogram, is proposed to address the problem of scale estimation under the framework of mean shift tracking. The target template is modelled with multi-scale model and described with three-dimensional spatial histogram. The tracking algorithm is implemented by three-dimensional mean shift iteration, which translates the problem of scale estimation in two-dimensional image plane into the localisation in three-dimensional image space. To enhance the robustness, the background weighted histogram is employed to suppress the background information in the target candidate model. Firstly, the multi-scale model and three-dimensional spatial histogram are introduced to represent the target template. Then, the three-dimensional mean shift iteration formulation is derived based on the similarity measure between the target model and the target candidate model. Finally, a multi-scale mean shift tracking algorithm combining multi-scale model and background weighted spatial histogram is proposed. The proposed algorithm is evaluated on some challenging sequences which contain scale changed targets and other complex appearance variations in comparison with three representative mean shift based tracking algorithms. Both the qualitative results and quantitative analysis indicate that the proposed algorithm outperforms the referenced algorithms in both tracking precision and scale estimation.

• 出版日期2015-2
• 单位中国人民解放军空军工程大学