Automatic tagging and geotagging in video collections and communities

M. Larson, M. Soleymani, P. Serdyukov, S. Rudinac, Christian Wartena, Vanessa Murdock, G. Friedland, R. Ordelman, Gareth J.F. Jones
{"title":"Automatic tagging and geotagging in video collections and communities","authors":"M. Larson, M. Soleymani, P. Serdyukov, S. Rudinac, Christian Wartena, Vanessa Murdock, G. Friedland, R. Ordelman, Gareth J.F. Jones","doi":"10.1145/1991996.1992047","DOIUrl":null,"url":null,"abstract":"Automatically generated tags and geotags hold great promise to improve access to video collections and online communities. We overview three tasks offered in the MediaEval 2010 benchmarking initiative, for each, describing its use scenario, definition and the data set released. For each task, a reference algorithm is presented that was used within MediaEval 2010 and comments are included on lessons learned. The Tagging Task, Professional involves automatically matching episodes in a collection of Dutch television with subject labels drawn from the keyword thesaurus used by the archive staff. The Tagging Task, Wild Wild Web involves automatically predicting the tags that are assigned by users to their online videos. Finally, the Placing Task requires automatically assigning geo-coordinates to videos. The specification of each task admits the use of the full range of available information including user-generated metadata, speech recognition transcripts, audio, and visual features.","PeriodicalId":390933,"journal":{"name":"Proceedings of the 1st ACM International Conference on Multimedia Retrieval","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"117","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st ACM International Conference on Multimedia Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1991996.1992047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 117

Abstract

Automatically generated tags and geotags hold great promise to improve access to video collections and online communities. We overview three tasks offered in the MediaEval 2010 benchmarking initiative, for each, describing its use scenario, definition and the data set released. For each task, a reference algorithm is presented that was used within MediaEval 2010 and comments are included on lessons learned. The Tagging Task, Professional involves automatically matching episodes in a collection of Dutch television with subject labels drawn from the keyword thesaurus used by the archive staff. The Tagging Task, Wild Wild Web involves automatically predicting the tags that are assigned by users to their online videos. Finally, the Placing Task requires automatically assigning geo-coordinates to videos. The specification of each task admits the use of the full range of available information including user-generated metadata, speech recognition transcripts, audio, and visual features.
视频集合和社区中的自动标记和地理标记
自动生成的标签和地理标签有望改善视频收藏和在线社区的访问。我们概述了MediaEval 2010基准测试计划中提供的三个任务,分别描述了它们的使用场景、定义和发布的数据集。对于每个任务,给出了在MediaEval 2010中使用的参考算法,并包含了对经验教训的评论。标签任务,专业涉及自动匹配集荷兰电视与主题标签从关键字同义词典绘制的档案工作人员使用。标记任务,Wild Wild Web涉及自动预测用户为其在线视频分配的标签。最后,放置任务需要自动为视频分配地理坐标。每个任务的规范允许使用所有可用信息,包括用户生成的元数据、语音识别抄本、音频和视觉特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信