A Kalman filtering based data fusion for object tracking

Chin Wen Wu, Yi Nung Chung, Pau Choo Chung

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

To solve that single camera has its limitation of field of view, this paper proposed an object tracking method using multiple camera data fusion in image sequences. In this approach, a tracking filter and a multiple-view data fusion algorithm are applied. An estimation structure, called hierarchical estimation, is used to generate local and global estimate and to combine the estimates obtained from each camera views to form a global estimate. The advantage of this approach is the data of one camera view complements that of another camera view in order to obtain better target measurement information and to make more accurate estimates. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that this approach successfully tracks objects and has good estimation.

原文English
主出版物標題Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
頁面2291-2295
頁數5
DOIs
出版狀態Published - 2010 九月 1
事件5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 - Taichung, Taiwan
持續時間: 2010 六月 152010 六月 17

Other

Other5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
國家Taiwan
城市Taichung
期間10-06-1510-06-17

    指紋

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

引用此

Wu, C. W., Chung, Y. N., & Chung, P. C. (2010). A Kalman filtering based data fusion for object tracking. 於 Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 (頁 2291-2295). [5516708] https://doi.org/10.1109/ICIEA.2010.5516708