{"title":"An exploration-based interface for interactive image retrieval","authors":"B. Thomee, M. Huiskes, E. Bakker, M. Lew","doi":"10.1109/ISPA.2009.5297746","DOIUrl":null,"url":null,"abstract":"One of the grand challenges in our field is considered to be the need for experiential exploration systems that allow the user to gain insight into and support exploration of media collections. In this paper we propose such a system, where a novel interface gives the user the opportunity to visually and interactively explore the feature space around relevant images and to focus the search on only those regions in feature space that are relevant. When an image is explored, its optimal set of feature weights is automatically determined using all images contained within the relevant regions, based on the evidential support for the relevance of each single feature. Images are ranked twofold, where one ranking reflects the likelihood the image is useful for further exploration of the feature space and the other reflects the likelihood the image is relevant to the user.","PeriodicalId":382753,"journal":{"name":"2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2009.5297746","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
One of the grand challenges in our field is considered to be the need for experiential exploration systems that allow the user to gain insight into and support exploration of media collections. In this paper we propose such a system, where a novel interface gives the user the opportunity to visually and interactively explore the feature space around relevant images and to focus the search on only those regions in feature space that are relevant. When an image is explored, its optimal set of feature weights is automatically determined using all images contained within the relevant regions, based on the evidential support for the relevance of each single feature. Images are ranked twofold, where one ranking reflects the likelihood the image is useful for further exploration of the feature space and the other reflects the likelihood the image is relevant to the user.