基于现有物体定位的无人值守和被盗物体检测

Waritchana Rakumthong, Natpaphat Phetcharaladakun, Wichuda Wealveerakup, N. Kamnoonwatana
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引用次数: 9

摘要

本文提出了一种新的设计和实现方法,以支持智能监控系统自动检测公交车站、火车站或机场等公共场所的遗弃和被盗物品。开发系统采用图像处理技术实现。在发现可疑事件(即无人看管或被盗物品)的情况下,系统会向负责该角色的人员(如保安或保安人员)发出警报。检测过程包括四个主要部分:1)视频采集2)视频处理3)事件检测4)结果呈现。进行实验的目的是为了获得以下质量:1)可用性:验证系统是否能够检测到对象并识别事件;2)正确性:衡量系统的准确性。最后,对数据集进行了测试,实验结果可以用百分比来衡量和表示系统的正确性。对象分类的正确率约为76%,事件分类的正确率为83%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unattended and stolen object detection based on relocating of existing object
This paper proposes a new design and implementation method in supporting a smart surveillance system that can automatically detect abandoned and stolen objects in public places such as bus stations, train stations or airports. The developing system is implemented by using image processing techniques. In the circumstance such as when suspicious events (i.e. left unattended or stolen objects) have been detected, the system will alert to people responsible for the role such as security guards or security staff. The detection process consists of four major components: 1) Video Acquisition 2) Video Processing 3) Event Detection and 4) Result Presentation. The experiment will be conducted in order to access the following qualities: 1) Usability: to verify that the system can detect the object and recognize the events, and 2) Correctness: to measure the accuracy of the system. Finally, the data sets are tested in the experimental result can measure and represent the correctness of system by percentage. The correctness of object classification is approximately 76%, and the correctness of event classification 83%.
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