{"title":"Integration of Points of Interest and Regions of Interest","authors":"Qi Li, Y. Gong, Y. Lu","doi":"10.1109/ChinaSIP.2014.6889266","DOIUrl":null,"url":null,"abstract":"Images consist of different low-level features, such as Points of Interest (POIs) and Regions of Interest (ROIs). A distinction between POIs and ROIs is that the latter ones have intrinsic scale information while the former ones may not have. In this paper, we propose a scheme to integrate these two kinds of image features. The proposed scheme optimizes feature distribution so that the optimized features become more compact. The scheme also assigns scale information to a POI via a stable association between the POI and a certain “nearest” ROI. We test the proposed integration scheme in terms of the repeatability across various imaging transformations. The experimental results demonstrate the effectiveness of the integration scheme.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ChinaSIP.2014.6889266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Images consist of different low-level features, such as Points of Interest (POIs) and Regions of Interest (ROIs). A distinction between POIs and ROIs is that the latter ones have intrinsic scale information while the former ones may not have. In this paper, we propose a scheme to integrate these two kinds of image features. The proposed scheme optimizes feature distribution so that the optimized features become more compact. The scheme also assigns scale information to a POI via a stable association between the POI and a certain “nearest” ROI. We test the proposed integration scheme in terms of the repeatability across various imaging transformations. The experimental results demonstrate the effectiveness of the integration scheme.