{"title":"兴趣点和兴趣区域的整合","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":"{\"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}","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}
Integration of Points of Interest and Regions of Interest
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.