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Transferring Training Instances for Convenient Cross-View Object Classification in Surveillance
Zhaoxiang Zhang; Yuhang Zhao; Yunhong Wang; Jianyun Liu; Zhenjun Yao; Jun Tang
2013-05-29
发表期刊IEEE Transactions on Information Forensics and Security
卷号8期号:10页码:1632-1641
摘要Automatic object classification is an important issue in traffic scene surveillance. Appearance variation due to perspective distortion is one of the most difficult problems for moving object detection, tracking, and recognition. We propose an active transfer learning approach to bridge the gap between appearance variations under two different scenes. Only a small number of training samples are required in the target scene, which can be combined with transferred samples of the source scene to achieve a reliable object classifier in the target scene, and active learning strategy makes the algorithm more efficient. Abundant experiments are conducted and experimental results demonstrate the effectiveness and convenience of our approach.
关键词Transfer Learning Active Learning Cross-view Object Classification Surveillance
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13202
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
推荐引用方式
GB/T 7714
Zhaoxiang Zhang,Yuhang Zhao,Yunhong Wang,et al. Transferring Training Instances for Convenient Cross-View Object Classification in Surveillance[J]. IEEE Transactions on Information Forensics and Security,2013,8(10):1632-1641.
APA Zhaoxiang Zhang,Yuhang Zhao,Yunhong Wang,Jianyun Liu,Zhenjun Yao,&Jun Tang.(2013).Transferring Training Instances for Convenient Cross-View Object Classification in Surveillance.IEEE Transactions on Information Forensics and Security,8(10),1632-1641.
MLA Zhaoxiang Zhang,et al."Transferring Training Instances for Convenient Cross-View Object Classification in Surveillance".IEEE Transactions on Information Forensics and Security 8.10(2013):1632-1641.
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