| 基于证据推理的高铁综合客运 枢纽客流图像背景建模 |
| |
| 引用本文： | 谢征宇,贾利民,秦勇,王力.基于证据推理的高铁综合客运 枢纽客流图像背景建模[J].北京理工大学学报,2012(S1):89-92. |
| |
| 作者姓名： | 谢征宇 贾利民 秦勇 王力 |
| |
| 作者单位： | 北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044;北京交通大学 交通运输学院, 北京 100044;北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044;北京交通大学 交通运输学院, 北京 100044;北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044;北京交通大学 交通运输学院, 北京 100044;北京交通大学 交通运输学院, 北京 100044 |
| |
| 基金项目： | 国家科技支撑计划项目(2009BAG12A10);国家部委重点资助课题(2012X013-A) |
| |
| 摘 要： | 针对高铁综合客运枢纽客流图像特征,提出基于证据推理的客流图像背景建模方法. 利用均值背景模型和灰度分区处理提高背景模型的处理速度,通过引入证据推理构建合适的mass函数,提高背景灰度值的取值范围的置信度,从而提高背景图像的精确性. 结果表明,该方法原理正确,在高铁综合客运枢纽客流安全预警实际应用中,能够快速准确地生成客流背景图像,保证了客流信息提取的速度和精度.
|
| 关 键 词： | 证据推理 灰度分区 背景建模 高铁综合客运枢纽 |
| 收稿时间： | 2012/9/28 0:00:00 |
Background Modeling of Passenger Flow Image in Comprehensive Passenger Transport Hub Based on Dempster-Shafer |
| |
| XIE Zheng-yu,JIA Li-min,QIN Yong and WANG Li.Background Modeling of Passenger Flow Image in Comprehensive Passenger Transport Hub Based on Dempster-Shafer[J].Journal of Beijing Institute of Technology(Natural Science Edition),2012(S1):89-92. |
| |
| Authors: | XIE Zheng-yu JIA Li-min QIN Yong and WANG Li |
| |
| Institution: | State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China |
| |
| Abstract: | A method was proposed to build background model of passenger flow image in comprehensive passenger transport hub based on dempster-shafer. Mean background model and gray area division were used to improve processing speed of background modeling. Mass function which was from Dempster-Shafer was used to improve confidence of background gray value area and accuracy of background image. Test results show that principle of the method is correct; passenger flow background image can be quickly and accurately built. This method insured the speed and precision of passenger flow information extraction in the passenger flow safety forewarning of high-speed railway comprehensive passenger transport hub. |
| |
| Keywords: | dempster-shafer gray area division background modeling comprehensive passenger transport hub |
|
| 点击此处可从《北京理工大学学报》浏览原始摘要信息 |
| 点击此处可从《北京理工大学学报》下载免费的PDF全文 |
|
