{"title":"Automatic YouTube-Thumbnail Generation and Its Evaluation","authors":"Akari Shimono, Yuki Kakui, T. Yamasaki","doi":"10.1145/3379173.3393711","DOIUrl":null,"url":null,"abstract":"YouTubers have recently become highly popular. Generating eye-catching thumbnails is an important factor in attracting viewers. In this study, we propose an automatic YouTube-video-thumbnail generation method that ensures the following: rich facial expression of the YouTuber in the frame, clear presentation of the subject of the video, and clear description of the content through a headline. We compared thumbnails generated by the proposed method with those generated by existing methods or those of actually posted videos (i.e., ground truth), and we evaluated the results.","PeriodicalId":416027,"journal":{"name":"Proceedings of the 2020 Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3379173.3393711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
YouTubers have recently become highly popular. Generating eye-catching thumbnails is an important factor in attracting viewers. In this study, we propose an automatic YouTube-video-thumbnail generation method that ensures the following: rich facial expression of the YouTuber in the frame, clear presentation of the subject of the video, and clear description of the content through a headline. We compared thumbnails generated by the proposed method with those generated by existing methods or those of actually posted videos (i.e., ground truth), and we evaluated the results.
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