{"title":"Automatic image retargeting with fisheye-view warping","authors":"Feng Liu, Michael Gleicher","doi":"10.1145/1095034.1095061","DOIUrl":null,"url":null,"abstract":"Image retargeting is the problem of adapting images for display on devices different than originally intended. This paper presents a method for adapting large images, such as those taken with a digital camera, for a small display, such as a cellular telephone. The method uses a non-linear fisheye-view warp that emphasizes parts of an image while shrinking others. Like previous methods, fisheye-view warping uses image information, such as low-level salience and high-level object recognition to find important regions of the source image. However, unlike prior approaches, a non-linear image warping function emphasizes the important aspects of the image while retaining the surrounding context. The method has advantages in preserving information content, alerting the viewer to missing information and providing robustness.","PeriodicalId":101797,"journal":{"name":"Proceedings of the 18th annual ACM symposium on User interface software and technology","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"204","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th annual ACM symposium on User interface software and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1095034.1095061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 204
Abstract
Image retargeting is the problem of adapting images for display on devices different than originally intended. This paper presents a method for adapting large images, such as those taken with a digital camera, for a small display, such as a cellular telephone. The method uses a non-linear fisheye-view warp that emphasizes parts of an image while shrinking others. Like previous methods, fisheye-view warping uses image information, such as low-level salience and high-level object recognition to find important regions of the source image. However, unlike prior approaches, a non-linear image warping function emphasizes the important aspects of the image while retaining the surrounding context. The method has advantages in preserving information content, alerting the viewer to missing information and providing robustness.