Research on semi-supervising learning algorithm for target model updating in target tracking

	Research on semi-supervising learning algorithm for target model updating in target tracking
	Wen, G.; T. Yang and Z. Ming
	2015
发表期刊	Acta Physica Sinica
卷号	64 期号:1 页码:9
摘要	Target detection and tracking technique is one of the hot subjects in image processing and computer vision fields, which has significant research value not only in military areas such as imaging guidance and military target tracking, but also for civil use such as security and monitoring and the intelligent man-machine interaction. In this paper, for target deformation, scale changing, rotation, and other issues in the long-term stable target tracking, a bootstrapping feedback learning algorithm is proposed, which may improve the target model and the classifier discriminating capacity as well as the fault tolerance ability; and it also makes fewer errors during the updating, and then the proof of convergence of the algorithm is given. Experimental results show that among the same tracking algorithms, utilization of the learning method to update the target model and classifier is more stable and more adaptable than unusing it in the processes of target scale changing, deformation, rotation, perspective changing and fuzzy. And compared with the existing conventional method, this method has a better robustness, and a high value in practical application and research.
收录类别	SCI ; EI
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/55548
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Wen, G.,T. Yang and Z. Ming. Research on semi-supervising learning algorithm for target model updating in target tracking[J]. Acta Physica Sinica,2015,64(1):9.
APA	Wen, G.,&T. Yang and Z. Ming.(2015).Research on semi-supervising learning algorithm for target model updating in target tracking.Acta Physica Sinica,64(1),9.
MLA	Wen, G.,et al."Research on semi-supervising learning algorithm for target model updating in target tracking".Acta Physica Sinica 64.1(2015):9.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
目标跟踪中目标模型更新问题的半监督学习算（7957KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载