摘要
The limitation of Mean Shift algorithm under crossing occlusion is analyzed. To solve this problem, a new tracking algorithm using Mean Shift with RBF neural network is proposed. According to the formal information about the object's location, the iteration start position is found with RBF neural network. And the object's real center is calculated by Mean Shift algorithm. Experimental results show that the proposal algorithm is stable to solve the crossing occlusion problem, and the iteration number is reduced.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Proceedings of the 27th Chinese Control Conference, CCC |
| 页 | 518-521 |
| 页数 | 4 |
| DOI | |
| 出版状态 | 已出版 - 2008 |
| 活动 | 27th Chinese Control Conference, CCC - Kunming, Yunnan, 中国 期限: 16 7月 2008 → 18 7月 2008 |
出版系列
| 姓名 | Proceedings of the 27th Chinese Control Conference, CCC |
|---|
会议
| 会议 | 27th Chinese Control Conference, CCC |
|---|---|
| 国家/地区 | 中国 |
| 市 | Kunming, Yunnan |
| 时期 | 16/07/08 → 18/07/08 |
指纹
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Zhou, B., Wang, J., & Mao, J. (2008). Algorithm of target tracking based on mean shift with RBF neural network. 在 Proceedings of the 27th Chinese Control Conference, CCC (页码 518-521). 文章 4605198 (Proceedings of the 27th Chinese Control Conference, CCC). https://doi.org/10.1109/CHICC.2008.4605198