Real-Time Moving Object Classification with Automatic Scene Division
文献类型：会议论文
| 作者 | Zhaoxiang Zhang ; Yinghao Cai; Kaiqi Huang; Tieniu Tan
|
| 出版日期 | 2007-09-16 |
| 会议名称 | IEEE International Conference on Image Processing |
| 会议日期 | 16-19 September 2007 |
| 会议地点 | San Antonio, Texas, USA |
| 关键词 | Surveillance Pattern classification Object recognition Motion detection Video signal processing |
| 通讯作者 | Zhaoxiang Zhang |
| 英文摘要 | We address the problem of moving object classification. Our aim is to classify moving objects of traffic scene videos into pedestrians, bicycles and vehicles. Instead of supervised learning and manual labeling of large training samples, our classifiers are initialized and refined online automatically. With efficient features extracted and organized, the approach can be real-time and achieve high classification accuracy. Once the view or scene changes detected, the algorithm can automatically refine the classifiers and adapt them to new environments. Experimental results demonstrate the effectiveness and robustness of the proposed approach. |
| 会议录 | 16 Sep - 19 Sep 2007
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10989]  |
| 专题 | 自动化研究所_09年以前成果 |
| 推荐引用方式 GB/T 7714 | Zhaoxiang Zhang,Yinghao Cai,Kaiqi Huang,et al. Real-Time Moving Object Classification with Automatic Scene Division[C]. 见:IEEE International Conference on Image Processing. San Antonio, Texas, USA. 16-19 September 2007. |
入库方式： OAI收割
来源：自动化研究所
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