Zhigang Hua, Chuang Wang, Xing Xie, Hanqing Lu, Wei-Ying Ma
{"title":"Automatic Annotation of Location Information for WWW Images","authors":"Zhigang Hua, Chuang Wang, Xing Xie, Hanqing Lu, Wei-Ying Ma","doi":"10.1109/ICME.2005.1521537","DOIUrl":null,"url":null,"abstract":"Currently, a crucial challenge is raised on how to manage a large amount of images on the Web. Due to a real synergy between an image and its location, we propose an automatic solution to annotate contextual location information for WWW images. We construct an image importance model to acquire the dominant images in a page that comprise contextual surrounding text. For each acquired image, we develop an effective algorithm to compute location from its contextual text. We apply our approach to 1,000 pages from various Websites for image location annotation. The experiments demonstrated that more than 30% WWW images are related with geographic location information, and our solution can achieve the satisfactory results. Finally, we present some potential applications involving the utilization of image location information","PeriodicalId":244360,"journal":{"name":"2005 IEEE International Conference on Multimedia and Expo","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Multimedia and Expo","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2005.1521537","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Currently, a crucial challenge is raised on how to manage a large amount of images on the Web. Due to a real synergy between an image and its location, we propose an automatic solution to annotate contextual location information for WWW images. We construct an image importance model to acquire the dominant images in a page that comprise contextual surrounding text. For each acquired image, we develop an effective algorithm to compute location from its contextual text. We apply our approach to 1,000 pages from various Websites for image location annotation. The experiments demonstrated that more than 30% WWW images are related with geographic location information, and our solution can achieve the satisfactory results. Finally, we present some potential applications involving the utilization of image location information