Huanxi Liu, Junchi Yan, Jun Zhu, Xiaowei Lv, Xiong Li, Tianhong Zhu, Yuncai Liu
{"title":"A Double-Layer Model for Foreground Detection from Video Sequence","authors":"Huanxi Liu, Junchi Yan, Jun Zhu, Xiaowei Lv, Xiong Li, Tianhong Zhu, Yuncai Liu","doi":"10.1109/ICIG.2011.33","DOIUrl":null,"url":null,"abstract":"This paper proposes a method for background modeling and foreground detection in video. This method divides the background into two layers, the dynamic layer and the static layer. An energy descriptor is proposed to analysis the motion state in dynamic layer while a grid filter is proposed to reduce the negative impact of sudden illumination change such as light switching off. Experiment results compared with four typical algorithms show that this method outperforms others in most challenging videos including sudden illumination change and some complex backgrounds.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Image and Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIG.2011.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a method for background modeling and foreground detection in video. This method divides the background into two layers, the dynamic layer and the static layer. An energy descriptor is proposed to analysis the motion state in dynamic layer while a grid filter is proposed to reduce the negative impact of sudden illumination change such as light switching off. Experiment results compared with four typical algorithms show that this method outperforms others in most challenging videos including sudden illumination change and some complex backgrounds.