{"title":"基于跟踪特征量化的视频检索","authors":"Hiroaki Kubo, Julien Pilet, H. Saito, S. Satoh","doi":"10.1109/ICPR.2010.794","DOIUrl":null,"url":null,"abstract":"In this paper, we present an image retrieval method based on feature tracking. Feature tracks are summarized into a compact discreet value and used for video indexing purpose. As opposed to existing space-time features, we do not make any assumption on the motion visible on the indexed videos. As a result, given an example query, our system is able to retrieve related videos from a large database. We evaluated our system with the copy detection benchmark MUSCLE-VCD-2007. We also ran retrieval experiment on hours of TV broadcast.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Video Retrieval Based on Tracked Features Quantization\",\"authors\":\"Hiroaki Kubo, Julien Pilet, H. Saito, S. Satoh\",\"doi\":\"10.1109/ICPR.2010.794\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an image retrieval method based on feature tracking. Feature tracks are summarized into a compact discreet value and used for video indexing purpose. As opposed to existing space-time features, we do not make any assumption on the motion visible on the indexed videos. As a result, given an example query, our system is able to retrieve related videos from a large database. We evaluated our system with the copy detection benchmark MUSCLE-VCD-2007. We also ran retrieval experiment on hours of TV broadcast.\",\"PeriodicalId\":309591,\"journal\":{\"name\":\"2010 20th International Conference on Pattern Recognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 20th International Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2010.794\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 20th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2010.794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video Retrieval Based on Tracked Features Quantization
In this paper, we present an image retrieval method based on feature tracking. Feature tracks are summarized into a compact discreet value and used for video indexing purpose. As opposed to existing space-time features, we do not make any assumption on the motion visible on the indexed videos. As a result, given an example query, our system is able to retrieve related videos from a large database. We evaluated our system with the copy detection benchmark MUSCLE-VCD-2007. We also ran retrieval experiment on hours of TV broadcast.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
