使用多媒体处理和集成个性化录像机

N. Dimitrova, R. Jasinschi, L. Agnihotri, J. Zimmerman, T. McGee, Dongge Li
{"title":"使用多媒体处理和集成个性化录像机","authors":"N. Dimitrova, R. Jasinschi, L. Agnihotri, J. Zimmerman, T. McGee, Dongge Li","doi":"10.1145/500141.500243","DOIUrl":null,"url":null,"abstract":"Current personal Vido recorders make it very easy for consumers to record whole TV programs. Our research however, focuses on personalizing TV at a sub-program level. We use a traditional Content-Based Information Retrieval system architecture consisting of archiving and retrieval modules. The archiving module employs a three-layered, multimodal integration framework to segment, analyze, characterize, and classify segments. The retrieval module relies on users personal preferences to deliver both full programs and video segments of interest. We tested retrieval concepts with real users and discovered that they see more value in segmenting non-narrative programs (e.g. news) than narrative programs (e.g. movies). We benchmarked individual algorithms and segment classification for celebrity and financial segments as instances of non-narrative content. For celebrity segments we obtained a total precision of 94.1% and recall of 85.7%, and for financial segments a total precision of 81.1% and a recall of 86.9%.","PeriodicalId":416848,"journal":{"name":"MULTIMEDIA '01","volume":"253 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Personalizing video recorders using multimedia processing and integration\",\"authors\":\"N. Dimitrova, R. Jasinschi, L. Agnihotri, J. Zimmerman, T. McGee, Dongge Li\",\"doi\":\"10.1145/500141.500243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Current personal Vido recorders make it very easy for consumers to record whole TV programs. Our research however, focuses on personalizing TV at a sub-program level. We use a traditional Content-Based Information Retrieval system architecture consisting of archiving and retrieval modules. The archiving module employs a three-layered, multimodal integration framework to segment, analyze, characterize, and classify segments. The retrieval module relies on users personal preferences to deliver both full programs and video segments of interest. We tested retrieval concepts with real users and discovered that they see more value in segmenting non-narrative programs (e.g. news) than narrative programs (e.g. movies). We benchmarked individual algorithms and segment classification for celebrity and financial segments as instances of non-narrative content. For celebrity segments we obtained a total precision of 94.1% and recall of 85.7%, and for financial segments a total precision of 81.1% and a recall of 86.9%.\",\"PeriodicalId\":416848,\"journal\":{\"name\":\"MULTIMEDIA '01\",\"volume\":\"253 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MULTIMEDIA '01\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/500141.500243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MULTIMEDIA '01","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/500141.500243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

现在的个人录像机使消费者很容易录下整个电视节目。然而,我们的研究主要集中在子节目层面的个性化电视。我们使用传统的基于内容的信息检索系统架构,包括归档和检索模块。归档模块采用三层多模态集成框架对数据段进行分段、分析、表征和分类。检索模块依赖于用户的个人偏好来提供完整的节目和感兴趣的视频片段。我们在真实用户身上测试了检索概念,发现他们认为分割非叙事节目(如新闻)比分割叙事节目(如电影)更有价值。我们将名人和金融细分作为非叙事内容的实例,对个别算法和细分分类进行基准测试。对于名人片段,我们获得了94.1%的总精度和85.7%的召回率,对于金融片段,我们获得了81.1%的总精度和86.9%的召回率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalizing video recorders using multimedia processing and integration
Current personal Vido recorders make it very easy for consumers to record whole TV programs. Our research however, focuses on personalizing TV at a sub-program level. We use a traditional Content-Based Information Retrieval system architecture consisting of archiving and retrieval modules. The archiving module employs a three-layered, multimodal integration framework to segment, analyze, characterize, and classify segments. The retrieval module relies on users personal preferences to deliver both full programs and video segments of interest. We tested retrieval concepts with real users and discovered that they see more value in segmenting non-narrative programs (e.g. news) than narrative programs (e.g. movies). We benchmarked individual algorithms and segment classification for celebrity and financial segments as instances of non-narrative content. For celebrity segments we obtained a total precision of 94.1% and recall of 85.7%, and for financial segments a total precision of 81.1% and a recall of 86.9%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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