{"title":"视频镜头分析采用高效多目标跟踪","authors":"V. V. Vinod, H. Murase","doi":"10.1109/MMCS.1997.609762","DOIUrl":null,"url":null,"abstract":"We present a method for analyzing video shots by tracking interesting objects in the video. Tracking employs efficient object search using upper bound pruning and statistical prediction of search area. The trades are analyzed to identify representative frames in shot and to build a concise representation. Experimental results on different types of video data are promising.","PeriodicalId":302885,"journal":{"name":"Proceedings of IEEE International Conference on Multimedia Computing and Systems","volume":"159 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Video shot analysis using efficient multiple object tracking\",\"authors\":\"V. V. Vinod, H. Murase\",\"doi\":\"10.1109/MMCS.1997.609762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a method for analyzing video shots by tracking interesting objects in the video. Tracking employs efficient object search using upper bound pruning and statistical prediction of search area. The trades are analyzed to identify representative frames in shot and to build a concise representation. Experimental results on different types of video data are promising.\",\"PeriodicalId\":302885,\"journal\":{\"name\":\"Proceedings of IEEE International Conference on Multimedia Computing and Systems\",\"volume\":\"159 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE International Conference on Multimedia Computing and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMCS.1997.609762\",\"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 IEEE International Conference on Multimedia Computing and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMCS.1997.609762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video shot analysis using efficient multiple object tracking
We present a method for analyzing video shots by tracking interesting objects in the video. Tracking employs efficient object search using upper bound pruning and statistical prediction of search area. The trades are analyzed to identify representative frames in shot and to build a concise representation. Experimental results on different types of video data are promising.