检索结果-南通市图书馆

A hierarchical clustering of features approach for vehicle tracking in traffic environments

International Journal of Intelligent Computing and Cybernetics 2016年第4期9卷 354-368页

作者： Anan Banharnsakun supannee tanathong CIR Laboratory Faculty of Engineering at SrirachaKasetsart University Sriracha CampusChonburiThailand Laboratory for Sensor and Modeling Department of GeoinformaticsUniversity of SeoulSeoulKorea

Purpose-Developing algorithms for automated detection and tracking of multiple objects is one challenge in the field of object *** in a traffic video monitoring system,vehicle detection is an essential and challenging *** the previous studies,many vehicle detection methods have been *** proposed approaches mostly used either motion information or characteristic information to detect *** these methods are effective in detecting vehicles,their detection accuracy still needs to be ***,the headlights and windshields,which are used as the vehicle features for detection in these methods,are easily obscured in some traffic *** paper aims to discuss these ***/methodology/approach-First,each frame will be captured from a video sequence and then the background subtraction is performed by using the Mixture-of-Gaussians background ***,the Shi-Tomasi corner detection method is employed to extract the feature points from objects of interest in each foreground scene and the hierarchical clustering approach is then applied to cluster and form them into feature *** feature blocks will be used to track the moving objects frame by ***-Using the proposed method,it is possible to detect the vehicles in both day-time and night-time scenarios with a 95 percent accuracy rate and can cope with irrelevant movement(waving trees),which has to be deemed as *** addition,the proposed method is able to deal with different vehicle shapes such as cars,vans,and ***/value-This paper presents a hierarchical clustering of features approach for multiple vehicles tracking in traffic environments to improve the capability of detection and tracking in case that the vehicle features are obscured in some traffic conditions.

关键词： Feature extraction Hierarchical clustering Mixture-of-Gaussians Multiple object detection Shi-Tomasi corner detection Vehicle tracking Background model

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：