Chin-Yang Lin, Wei-Wen Chang, Panyaporn Prangjarote, C. Yeh, Guo-Shiang Lin
{"title":"Alleviating cavity problems in moving object detection based on hysteresis thresholding and multi-models","authors":"Chin-Yang Lin, Wei-Wen Chang, Panyaporn Prangjarote, C. Yeh, Guo-Shiang Lin","doi":"10.1109/ISCE.2013.6570179","DOIUrl":null,"url":null,"abstract":"Traditional background modeling methods often require complicated computations and suffer from cavity problems in foreground objects. In this paper, we propose a block-based background modeling method combining multiple detection results derived from color and texture characteristics. This method can significantly alleviate the cavity problem and resist certain shadow interference. Since the proposed scheme only requires low complexity, it is suitable for real-time applications.","PeriodicalId":442380,"journal":{"name":"2013 IEEE International Symposium on Consumer Electronics (ISCE)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Symposium on Consumer Electronics (ISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCE.2013.6570179","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
Traditional background modeling methods often require complicated computations and suffer from cavity problems in foreground objects. In this paper, we propose a block-based background modeling method combining multiple detection results derived from color and texture characteristics. This method can significantly alleviate the cavity problem and resist certain shadow interference. Since the proposed scheme only requires low complexity, it is suitable for real-time applications.