视频高光镜头提取与时间同步评论

Yikun Xian, Jiangfeng Li, Chenxi Zhang, Zhenyu A. Liao
{"title":"视频高光镜头提取与时间同步评论","authors":"Yikun Xian, Jiangfeng Li, Chenxi Zhang, Zhenyu A. Liao","doi":"10.1145/2757513.2757516","DOIUrl":null,"url":null,"abstract":"Benefit from abundance of mobile applications, portability of large-screen mobile devices and accessibility of media resources, users nowadays much more prefer to watch videos on their mobiles no matter whether they are at home or on the way. However, constrained by available time and network flow, users may only choose to watch some hot video segments that are manually annotated by video editors. In this paper, we aim to automatically extract video highlight shot with the help of video sentimental feature of time-sync comments. First, analyzing statistical feature of real data. After, we simulate the generation process of time-sync comment after. Then, we propose a shot boundary detection method to extract highlight shot, which is proved to be more effective than traditional methods based on comment density. This experiment attests the time-sync comment is particularly suitable for sentiment-based video segment extraction for 2 reasons. 1) Text-based similarity calculation of is much faster than image-based process depending on every frame of video; 2) Time-sync comment reflects user subjective emotion therefore is useful in personalised video recommendation.","PeriodicalId":102278,"journal":{"name":"Proceedings of the 7th International Workshop on Hot Topics in Planet-scale mObile computing and online Social neTworking","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Video Highlight Shot Extraction with Time-Sync Comment\",\"authors\":\"Yikun Xian, Jiangfeng Li, Chenxi Zhang, Zhenyu A. Liao\",\"doi\":\"10.1145/2757513.2757516\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Benefit from abundance of mobile applications, portability of large-screen mobile devices and accessibility of media resources, users nowadays much more prefer to watch videos on their mobiles no matter whether they are at home or on the way. However, constrained by available time and network flow, users may only choose to watch some hot video segments that are manually annotated by video editors. In this paper, we aim to automatically extract video highlight shot with the help of video sentimental feature of time-sync comments. First, analyzing statistical feature of real data. After, we simulate the generation process of time-sync comment after. Then, we propose a shot boundary detection method to extract highlight shot, which is proved to be more effective than traditional methods based on comment density. This experiment attests the time-sync comment is particularly suitable for sentiment-based video segment extraction for 2 reasons. 1) Text-based similarity calculation of is much faster than image-based process depending on every frame of video; 2) Time-sync comment reflects user subjective emotion therefore is useful in personalised video recommendation.\",\"PeriodicalId\":102278,\"journal\":{\"name\":\"Proceedings of the 7th International Workshop on Hot Topics in Planet-scale mObile computing and online Social neTworking\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 7th International Workshop on Hot Topics in Planet-scale mObile computing and online Social neTworking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2757513.2757516\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th International Workshop on Hot Topics in Planet-scale mObile computing and online Social neTworking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2757513.2757516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

得益于丰富的移动应用程序、大屏幕移动设备的便携性以及媒体资源的可访问性,如今的用户无论是在家还是在路上,都更喜欢在手机上观看视频。然而,受时间和网络流量的限制,用户可能只会选择观看视频编辑人工标注的一些热门视频片段。本文旨在利用时间同步评论的视频情感特征,实现视频亮点镜头的自动提取。首先,分析实际数据的统计特征。之后,我们模拟了时间同步注释的生成过程。然后,我们提出了一种镜头边界检测方法来提取高光镜头,事实证明该方法比传统的基于评论密度的方法更有效。本实验证明了时间同步评论特别适合于基于情感的视频片段提取,原因有二。1)基于文本的相似性计算比基于图像的基于视频每帧的相似性计算快得多;2)时间同步评论反映了用户的主观情绪,因此在个性化视频推荐中很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Video Highlight Shot Extraction with Time-Sync Comment
Benefit from abundance of mobile applications, portability of large-screen mobile devices and accessibility of media resources, users nowadays much more prefer to watch videos on their mobiles no matter whether they are at home or on the way. However, constrained by available time and network flow, users may only choose to watch some hot video segments that are manually annotated by video editors. In this paper, we aim to automatically extract video highlight shot with the help of video sentimental feature of time-sync comments. First, analyzing statistical feature of real data. After, we simulate the generation process of time-sync comment after. Then, we propose a shot boundary detection method to extract highlight shot, which is proved to be more effective than traditional methods based on comment density. This experiment attests the time-sync comment is particularly suitable for sentiment-based video segment extraction for 2 reasons. 1) Text-based similarity calculation of is much faster than image-based process depending on every frame of video; 2) Time-sync comment reflects user subjective emotion therefore is useful in personalised video recommendation.
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:481959085
Book学术官方微信