التفاصيل البيبلوغرافية
| العنوان: |
Adaptive structured sub-blocks tracking. |
| المؤلفون: |
Liu, Jing-Wen1 M201272672@hust.edu.cn, Sun, Wei-Ping1 wpsun@hust.edu.cn, Xia, Tao1 xiatao@hust.edu.cn |
| المصدر: |
Neurocomputing. Sep2016, Vol. 204, p97-105. 9p. |
| مصطلحات موضوعية: |
*SMART structures, *ALGORITHMS, *DEFORMATION of surfaces, *MONTE Carlo method, *EYE tracking |
| مستخلص: |
Visual object tracking algorithms based on middle level appearance have been widely studied for their effective representation to non-rigid appearance variation and partial occlusion. Sub-blocks are often adopted as local feature in mid-level based tracking algorithms. How to select representative sub-blocks to reveal the spatial structure of objects and retain the flexibility to model non-rigid deformation has not been adequately addressed. Exploiting discrimination, uniqueness and historical prediction accuracy of sub-blocks of a target, we propose a local feature selection method which includes rough initial subblock selection and refined subblock-sample particle bi-directional selection under particle filter tracking framework. A quantitative evaluation is conducted on 10 sequences. Experimental results show the robustness of our proposed algorithm in tackling with non-rigid deformation and partial occlusion. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
