Region Covariance Based Probabilistic Tracking
文献类型：会议论文
| 作者 | Hanqing Hu ; Jianzhao Qin ; Yaping Lin ; Yangsheng Xu |
| 出版日期 | 2008 |
| 会议名称 | Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08 |
| 会议地点 | Chongqing, China |
| 英文摘要 | Region covariance descriptor recently proposed in [2] has been approved robust and elegant to describe a region of interest which has been applied to visual tracking [1]. By employing region covariance descriptor, the tracker efficiently fuses multiple features and modalities and has a capacity for comparing regions with different window sizes. Relying on the same principle of region covariance descriptor, but with a probabilisticframework, we introduce an elegant way to integrate covariance descriptor into Mont Carlo tracking technique for visual tracking. The advantages of particle filter and multiple features of region covariance descriptor entitle us better competence to handle object tracking within complex environment, as well as partial and completed occlusions of the tracked entity over a few frames. The experimental results show that regioncovariance based particle tracker outperforms CAMSHIFT tracker and color based particle tracker within complex environment. And our tracker also better handles occlusions when comparing with region covariance descriptor based local search tracker. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/2231]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 推荐引用方式 GB/T 7714 | Hanqing Hu,Jianzhao Qin,Yaping Lin,et al. Region Covariance Based Probabilistic Tracking[C]. 见:Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08. Chongqing, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
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