{"title":"Automatic image cropping using sparse coding","authors":"Jieying She, Duo-Chao Wang, Mingli Song","doi":"10.1109/ACPR.2011.6166623","DOIUrl":null,"url":null,"abstract":"Image cropping is a technique to help people improve their taken photos' quality by discarding unnecessary parts of a photo. In this paper, we propose a new approach to crop the photo for better composition through learning the structure. Firstly, we classify photos into different categories. Then we extract the graph-based visual saliency map of these photos, based on which we build a dictionary for each categories. Finally, by solving the sparse coding problem of each input photo based on the dictionary, we find a cropped region that can be best decoded by this dictionary. The experimental results demonstrate that our technique is applicable to a wide range of photos and produce more agreeable resulting photos.","PeriodicalId":287232,"journal":{"name":"The First Asian Conference on Pattern Recognition","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The First Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2011.6166623","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
Image cropping is a technique to help people improve their taken photos' quality by discarding unnecessary parts of a photo. In this paper, we propose a new approach to crop the photo for better composition through learning the structure. Firstly, we classify photos into different categories. Then we extract the graph-based visual saliency map of these photos, based on which we build a dictionary for each categories. Finally, by solving the sparse coding problem of each input photo based on the dictionary, we find a cropped region that can be best decoded by this dictionary. The experimental results demonstrate that our technique is applicable to a wide range of photos and produce more agreeable resulting photos.