运动轨迹重建度:监控视频的关键帧选择标准

IF 1 4区 计算机科学 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Yunzuo Zhang, Yameng Liu, Jiayu Zhang, Shasha Zhang, Shuangshuang Wang, Yu Cheng
{"title":"运动轨迹重建度:监控视频的关键帧选择标准","authors":"Yunzuo Zhang, Yameng Liu, Jiayu Zhang, Shasha Zhang, Shuangshuang Wang, Yu Cheng","doi":"10.1117/1.jei.33.3.033009","DOIUrl":null,"url":null,"abstract":"The primary focus of key frame extraction lies in extracting changes in the motion state from surveillance videos and considering them to be crucial content. However, existing key frame evaluation indicators cannot accurately assess whether the algorithm can capture them. Hence, key frame extraction methods are assessed from the viewpoint of target trajectory reconstruction. The motion trajectory reconstruction degree (MTRD), a key frame selection criterion based on maintaining target global and local motion information, is then put forth. Initially, this evaluation indicator extracts key frames using various key frame extraction methods and reconstructs the motion trajectory based on these key frames using a linear interpolation algorithm. Then, the original motion trajectories of the target are quantified and compared with the reconstructed set of motion trajectories. The more minor the MTRD discrepancy is, the better the trajectory overlap is, and the more accurate the key frames extracted with this method will be for the description of the video content. Finally, inspired by the novel MTRD criterion, we develop an MTRD-oriented key frame extraction method for the surveillance video. The outcomes of the simulations demonstrate that MTRD can more accurately capture the variations in the global and local motion states and is more compatible with the human visual perception.","PeriodicalId":54843,"journal":{"name":"Journal of Electronic Imaging","volume":"37 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Motion trajectory reconstruction degree: a key frame selection criterion for surveillance video\",\"authors\":\"Yunzuo Zhang, Yameng Liu, Jiayu Zhang, Shasha Zhang, Shuangshuang Wang, Yu Cheng\",\"doi\":\"10.1117/1.jei.33.3.033009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The primary focus of key frame extraction lies in extracting changes in the motion state from surveillance videos and considering them to be crucial content. However, existing key frame evaluation indicators cannot accurately assess whether the algorithm can capture them. Hence, key frame extraction methods are assessed from the viewpoint of target trajectory reconstruction. The motion trajectory reconstruction degree (MTRD), a key frame selection criterion based on maintaining target global and local motion information, is then put forth. Initially, this evaluation indicator extracts key frames using various key frame extraction methods and reconstructs the motion trajectory based on these key frames using a linear interpolation algorithm. Then, the original motion trajectories of the target are quantified and compared with the reconstructed set of motion trajectories. The more minor the MTRD discrepancy is, the better the trajectory overlap is, and the more accurate the key frames extracted with this method will be for the description of the video content. Finally, inspired by the novel MTRD criterion, we develop an MTRD-oriented key frame extraction method for the surveillance video. The outcomes of the simulations demonstrate that MTRD can more accurately capture the variations in the global and local motion states and is more compatible with the human visual perception.\",\"PeriodicalId\":54843,\"journal\":{\"name\":\"Journal of Electronic Imaging\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Electronic Imaging\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1117/1.jei.33.3.033009\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Electronic Imaging","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1117/1.jei.33.3.033009","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

关键帧提取的主要重点在于从监控视频中提取运动状态的变化,并将其视为关键内容。然而,现有的关键帧评价指标无法准确评估算法是否能捕捉到关键帧。因此,关键帧提取方法要从目标轨迹重构的角度进行评估。运动轨迹重构度(MTRD)是一种基于保持目标全局和局部运动信息的关键帧选择标准。首先,该评价指标使用各种关键帧提取方法提取关键帧,并根据这些关键帧使用线性插值算法重建运动轨迹。然后,对目标的原始运动轨迹进行量化,并与重建的运动轨迹集进行比较。MTRD 差异越小,轨迹重叠越好,用这种方法提取的关键帧对视频内容的描述就越准确。最后,在新颖的 MTRD 准则的启发下,我们开发了一种面向 MTRD 的监控视频关键帧提取方法。模拟结果表明,MTRD 可以更准确地捕捉全局和局部运动状态的变化,并且更符合人类的视觉感知。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motion trajectory reconstruction degree: a key frame selection criterion for surveillance video
The primary focus of key frame extraction lies in extracting changes in the motion state from surveillance videos and considering them to be crucial content. However, existing key frame evaluation indicators cannot accurately assess whether the algorithm can capture them. Hence, key frame extraction methods are assessed from the viewpoint of target trajectory reconstruction. The motion trajectory reconstruction degree (MTRD), a key frame selection criterion based on maintaining target global and local motion information, is then put forth. Initially, this evaluation indicator extracts key frames using various key frame extraction methods and reconstructs the motion trajectory based on these key frames using a linear interpolation algorithm. Then, the original motion trajectories of the target are quantified and compared with the reconstructed set of motion trajectories. The more minor the MTRD discrepancy is, the better the trajectory overlap is, and the more accurate the key frames extracted with this method will be for the description of the video content. Finally, inspired by the novel MTRD criterion, we develop an MTRD-oriented key frame extraction method for the surveillance video. The outcomes of the simulations demonstrate that MTRD can more accurately capture the variations in the global and local motion states and is more compatible with the human visual perception.
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
Journal of Electronic Imaging
Journal of Electronic Imaging 工程技术-成像科学与照相技术
CiteScore
1.70
自引率
27.30%
发文量
341
审稿时长
4.0 months
期刊介绍: The Journal of Electronic Imaging publishes peer-reviewed papers in all technology areas that make up the field of electronic imaging and are normally considered in the design, engineering, and applications of electronic imaging systems.
×
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