{"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}
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.
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.