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一种快速相似视频检索方法 被引量：1

A Fast Similarity-based Video Retrieval
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摘要 为了解决相似性视频检索中相似性度量和快速检索两个难题,本文提出了一种新的相似性视频快速检索方法.从视觉相似性出发,根据视频的时空分布特征统计计算压缩视频签名,通过视频签名的距离度量视频相似性.为了适应可扩展计算的需要,提出了基于聚类索引表的检索方法.通过对大规模数据库的查询测试结果证明该相似性检索算法快速有效. To solve two challenging problems in similarity-based video retrieval：similarity measurement and fast search,a novel similarity-based video approach is proposed.A compact video signature is computed based on the statistics of spatial-temporal features of video according to visual similarity.The video similarity is measured by the computation distance of video signature.For the scalable computing requirement,a search method via clustering index table is presented.The results from the query tests in large database show that this similarity retrieval method is fast and efficient.
作者 曹政 卢宝丰 朱明
机构地区 中国科学技术大学自动化系 中国科学院网络传播系统与控制重点实验室网络传播系统与控制安徽省重点实验室 上海文广互动电视有限公司
出处 《信息与控制》 CSCD 北大核心 2010年第5期635-639,共5页 Information and Control
基金 国家863计划资助项目(2008AA01A318) 国家自然科学基金资助项目(60975045)
关键词 相似视频 视频签名 时空分布特征 聚类索引表 similarity-based video video signature spatial-temporal feature clustering index table
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献12

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同被引文献18

  • 1Chen L,Chua T S.A match and tiling approach to content-basedvideo retrieval[C]∥Int.Conf.on Multimedia and Expo.2001:417-420.
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  • 3Chiu C,Wang H.A novel video matching framework for copy detection[C]∥Proc.of the 21th IPPR Conference on Computer Vision,Graphics and Image Processing (CVGIP’2008).2008.
  • 4Myers C S,Rabiner L R.A comparative study of several dynamictime-warping algorithms for connected word recognition[J].The Bell System Technical Journal,1981,60(7):1389-1409.
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  • 6Chen T,Jiang S,Chu L,et al.Detection and location of near-duplicate video sub-clips by finding dense subgraphs[C]∥Procee-dings of the 19th ACM international conference on Multimedia.ACM,2011:1173-1176.
  • 7Lowe D G.Distinctive image features from scale-invariant keypoints[J].International journal of computer vision,2004,60(2):91-110.
  • 8Bay H,Tuytelaars T,Van Gool L.Surf:Speeded up robust features[M].Computer Vision-ECCV 2006.Springer Berlin Heidelberg,2006:404-417.
  • 9Rosten E,Drummond T.Machine learning for high-speed corner detection[M]∥Computer Vision-ECCV 2006.Springer Berlin Heidelberg,2006:430-443.
  • 10Calonder M,Lepetit V,Strecha C,et al.BRIEF:binary robustindependent elementary features[M]∥Computer Vision-ECCV 2010.Springer Berlin Heidelberg,2010:778-792.

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信息与控制
2010年 第5期

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