Real-time moving object detection under complex background

Jinchang Ren, P. Astheimer, D. Feng
{"title":"Real-time moving object detection under complex background","authors":"Jinchang Ren, P. Astheimer, D. Feng","doi":"10.1109/ISPA.2003.1296359","DOIUrl":null,"url":null,"abstract":"Moving object detection (MOD) is a basic and important problem in video analysis and vision applications. In this paper, a novel MOD method is proposed using global motion estimation and edge information. In order to get more robust MOD results under different backgrounds and lighting conditions, a bilinear model and histogram scaling method are used respectively for spatial and illumination normalization. After normalization, edges are extracted by Canny and further filtered using morphological operators to get closed object contours. The final objects are extracted by combining the contours and moving regions from motion detection. The experimental results show the proposed approach has apparent advantages in robust and accurate detection and tracking of moving objects with changing of camera positions, lighting conditions and background for real-time applications.","PeriodicalId":218932,"journal":{"name":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2003.1296359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

Moving object detection (MOD) is a basic and important problem in video analysis and vision applications. In this paper, a novel MOD method is proposed using global motion estimation and edge information. In order to get more robust MOD results under different backgrounds and lighting conditions, a bilinear model and histogram scaling method are used respectively for spatial and illumination normalization. After normalization, edges are extracted by Canny and further filtered using morphological operators to get closed object contours. The final objects are extracted by combining the contours and moving regions from motion detection. The experimental results show the proposed approach has apparent advantages in robust and accurate detection and tracking of moving objects with changing of camera positions, lighting conditions and background for real-time applications.
复杂背景下实时运动目标检测
运动目标检测是视频分析和视觉应用中的一个基本而重要的问题。本文提出了一种基于全局运动估计和边缘信息的建模方法。为了在不同背景和光照条件下获得更鲁棒的MOD结果,分别采用双线性模型和直方图缩放方法对空间和光照进行归一化。归一化后,用Canny提取边缘,再用形态学算子进一步滤波得到闭合的目标轮廓。结合运动检测得到的轮廓和运动区域提取最终目标。实验结果表明,该方法在实时应用中对摄像机位置、光照条件和背景变化的运动目标具有鲁棒性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信