文章基本信息

标题：The Research of Event Detection and Characterization Technology of Ticket Gate in the Urban Rapid Rail Transit
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作者：Yunfeng Hou , Chaoli Wang * , Yunfeng Ji
期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2015
卷号：08
期号：01
页码：6-15
DOI：10.4236/jsea.2015.81002
语种：English
出版社：Scientific Research Publishing
摘要：Making events recognition more reliable under complex environment is one of the most important challenges for the intelligent recognition system to the ticket gate in the urban rapid rail transit. The motion objects passing through the ticket gate could be described as a series of moving sequences got by sensors that located in the walkway side of the ticket gate. This paper presents a robust method to detect some classes of events of ticket gate in the urban rapid rail transit. Diffused reflectance infrared sensors are used to collect signals. In this paper, the motion objects are here referred to passenger(s) or (and) luggage(s), for which are of frequent occurrences in the ticket gate of the urban railway traffic. Specifically, this paper makes two main contributions: 1) The proposed recognition method could be used to identify several events, including the event of one person passing through the ticket gate, the event of two consecutive passengers passing through the ticket gate without a big gap between them, and the event of a passenger walking through the ticket gate pulling a suitcase; 2) The moving time sequence matrix is transformed into a one-dimensional vector as the feature descriptor. Deep learning (DL), back propagation neural network (BP), and support vector machine (SVM) are applied to recognize the events respectively. BP has been proved to have a higher recognition rate compared to other methods. In order to implement the three algorithms, a data set is built which includes 150 samples of all kinds of events from the practical tests. Experiments show the effectiveness of the proposed methods.
关键词：Intelligent Recognition; Ticket Gate; Motion Objects; Infrared Sensors; Time Sequence