Object Tracking Based on Multi-feature Mean-shift Algorithm
Jiafu Jiang, Hui Xiong
Available Online November 2012.
- https://doi.org/10.2991/citcs.2012.149How to use a DOI?
- object trackingn; Mean-shift; color-texture histogram;Kalman
- Object tracking is one of the key technologies in intelligent video surveillance and how to describe the moving target is a key issue. Traditional color histogram Mean-shift (MS) algorithm only considered object's color statistical information, and didn't contain object's space information, so when the object color was close to the background color, the traditional MS algorithm easily caused object tracking inaccurately or lost. To solve this problem, a novel object tracking algorithm which based on improved MS and Kalman was proposed in this paper. Firstly, using the joint color-texture histogram to represent a target and applying it to the MS framework, then the improved MS goes for a small range of search and target match according to the result of Kalman prediction. The experimental results show that our algorithm tracking the object accurately and effectively even though the object color was close to the background color or the target moves fast.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jiafu Jiang AU - Hui Xiong PY - 2012/11 DA - 2012/11 TI - Object Tracking Based on Multi-feature Mean-shift Algorithm BT - 2012 National Conference on Information Technology and Computer Science PB - Atlantis Press SP - 579 EP - 582 SN - 1951-6851 UR - https://doi.org/10.2991/citcs.2012.149 DO - https://doi.org/10.2991/citcs.2012.149 ID - Jiang2012/11 ER -