Active Learning for Transferrable Object Classification in Cross-View Traffic Scene Surveillance
文献类型：会议论文
| 作者 | Zhaoxiang Zhang ; Jun Tang; Yuhang Zhao; Yunhong Wang
|
| 出版日期 | 2012-12-04 |
| 会议日期 | 4-6 December 2012 |
| 会议地点 | Singapore, Singapore |
| 关键词 | Active Transfer Learning Object Classification Visual Surveillance |
| 英文摘要 | We discuss the problem of object classification in cross-view traffic scene surveillance videos in this paper. To classify moving objects in traffic scene videos into pedestrian, bicycle and variety of vehicles, an effective intelligent classification framework has been proposed which takes advantage of a transfer machine learning method to bridge the gap between source scene data and target scene data. The transfer learning algorithm makes one classifier adaptive to perspective changes instead of training two different classifiers for corresponding perspectives. The samples transferred from source scene database have saved much manual labeling work on target scene database. In this paper, we propose an active transfer learning method to decrease manual labeling work further for target scene traffic object classification. Redundant experiments are conducted and experimental results demonstrate the effectiveness and convenience of our approach. |
| 会议录 | PCM 2012
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13246]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Zhaoxiang Zhang |
| 推荐引用方式 GB/T 7714 | Zhaoxiang Zhang,Jun Tang,Yuhang Zhao,et al. Active Learning for Transferrable Object Classification in Cross-View Traffic Scene Surveillance[C]. 见:. Singapore, Singapore. 4-6 December 2012. |
入库方式： OAI收割
来源：自动化研究所
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