{"title":"多媒体流实时查询系统","authors":"B. Liu, Amarnath Gupta, R. Jain","doi":"10.1145/1160939.1160950","DOIUrl":null,"url":null,"abstract":"Querying live media streams captured by various sensors is becoming a challenging problem, due to the data heterogeneity and the lack of a unifying data model capable of accessing various multimedia data and providing reasonable abstractions for the query purpose. In this paper we propose a system that enables directly capturing media streams from sensors and automatically generating more meaningful feature streams that can be queried by a data stream processor. The system provides an effective combination between extendible digital processing techniques and general data stream management research.","PeriodicalId":346313,"journal":{"name":"Computer Vision meets Databases","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A live multimedia stream querying system\",\"authors\":\"B. Liu, Amarnath Gupta, R. Jain\",\"doi\":\"10.1145/1160939.1160950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Querying live media streams captured by various sensors is becoming a challenging problem, due to the data heterogeneity and the lack of a unifying data model capable of accessing various multimedia data and providing reasonable abstractions for the query purpose. In this paper we propose a system that enables directly capturing media streams from sensors and automatically generating more meaningful feature streams that can be queried by a data stream processor. The system provides an effective combination between extendible digital processing techniques and general data stream management research.\",\"PeriodicalId\":346313,\"journal\":{\"name\":\"Computer Vision meets Databases\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Vision meets Databases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1160939.1160950\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Vision meets Databases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1160939.1160950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Querying live media streams captured by various sensors is becoming a challenging problem, due to the data heterogeneity and the lack of a unifying data model capable of accessing various multimedia data and providing reasonable abstractions for the query purpose. In this paper we propose a system that enables directly capturing media streams from sensors and automatically generating more meaningful feature streams that can be queried by a data stream processor. The system provides an effective combination between extendible digital processing techniques and general data stream management research.
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