{"title":"Computer vision framework for object monitoring","authors":"T. Wiangtong, S. Prongnuch","doi":"10.1109/ECTICON.2012.6254291","DOIUrl":null,"url":null,"abstract":"This paper presents the use of Visual C++ integrated with OpenCV library as a framework for video analysis applications. Conventionally, applications are developed and control using textual-based Win32 console. In this work, however, the library can be applied in Windows form that helps users to visually control algorithms implemented in applications. The framework, written in OOP style, tailors the existing library into three main class methods; initializing, running and ending. Streaming data can be captured from USB cameras, IP cameras and video files. Implementing computer vision algorithms include object counting and object monitoring is demonstrated. Results show that algorithms work well and they can be developed in short time.","PeriodicalId":6319,"journal":{"name":"2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology","volume":"35 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECTICON.2012.6254291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

This paper presents the use of Visual C++ integrated with OpenCV library as a framework for video analysis applications. Conventionally, applications are developed and control using textual-based Win32 console. In this work, however, the library can be applied in Windows form that helps users to visually control algorithms implemented in applications. The framework, written in OOP style, tailors the existing library into three main class methods; initializing, running and ending. Streaming data can be captured from USB cameras, IP cameras and video files. Implementing computer vision algorithms include object counting and object monitoring is demonstrated. Results show that algorithms work well and they can be developed in short time.
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用于对象监控的计算机视觉框架
本文介绍了使用Visual c++集成OpenCV库作为视频分析应用的框架。传统上,应用程序是使用基于文本的Win32控制台开发和控制的。然而,在这项工作中,该库可以以Windows形式应用,帮助用户可视化地控制应用程序中实现的算法。该框架以面向对象风格编写,将现有库裁剪为三个主要的类方法;初始化、运行和结束。流数据可以从USB摄像机,IP摄像机和视频文件捕获。实现计算机视觉算法包括目标计数和目标监控。结果表明,该算法运行良好,可在短时间内开发完成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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