{"title":"基于块统计的时间纹理视频索引与检索方法","authors":"A. Rahman, M. Murshed, L. Dooley","doi":"10.1109/INCC.2004.1366593","DOIUrl":null,"url":null,"abstract":"A new unified video indexing and retrieval method is presented to classify temporal texture videos using spatial as well as temporal cooccurrence statistics of block-based motion vectors, so keeping the computational complexity for retrieval within a real-time bound. Experimental results clearly demonstrate the superiority of the proposed method over existing temporal cooccurrence matrix-based solutions.","PeriodicalId":337263,"journal":{"name":"2004 International Networking and Communication Conference","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A new video indexing and retrieval method for temporal textures using block-based cooccurrence statistics\",\"authors\":\"A. Rahman, M. Murshed, L. Dooley\",\"doi\":\"10.1109/INCC.2004.1366593\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new unified video indexing and retrieval method is presented to classify temporal texture videos using spatial as well as temporal cooccurrence statistics of block-based motion vectors, so keeping the computational complexity for retrieval within a real-time bound. Experimental results clearly demonstrate the superiority of the proposed method over existing temporal cooccurrence matrix-based solutions.\",\"PeriodicalId\":337263,\"journal\":{\"name\":\"2004 International Networking and Communication Conference\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 International Networking and Communication Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INCC.2004.1366593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Networking and Communication Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INCC.2004.1366593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new video indexing and retrieval method for temporal textures using block-based cooccurrence statistics
A new unified video indexing and retrieval method is presented to classify temporal texture videos using spatial as well as temporal cooccurrence statistics of block-based motion vectors, so keeping the computational complexity for retrieval within a real-time bound. Experimental results clearly demonstrate the superiority of the proposed method over existing temporal cooccurrence matrix-based solutions.
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