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基于镜头竞争力的多模态视频场景分割算法

Multi-Modality Video Scene Segmentation Algorithm Based on Shot Force Competition
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摘要 为了能快速、有效地进行视频场景分割,论文提出一种基于镜头竞争力的多模态视频场景分割算法,充分考虑视频中多模态之间的时序关联共生特性,通过对视频物理特征的提取、融合计算出镜头间相似度,结合镜头竞争力的判定思想分割出视频场景。实验结果表明,该算法能较为高效地进行视频场景分割,查全率和查准率可达82.1%和86.7%。 In order to quickly and effectively video scene segmentation,a multi-modality video scene segmentation algo rithm based on shot force competition is proposed realize.Take full account of temporal associated co-occurrence of multimodal media data in video,the video shot similarity is calculated by extracting and merging the video physical features,and shot competitive judgment method is combined to conduct video scene segmentation.The experiments show that the video scene can be effectively separated by the proposed method,and recall,precision reach 82.1 %,86.7% respectively.
作者 向云柱
出处 《计算机与数字工程》 2014年第2期296-299,共4页 Computer & Digital Engineering
基金 湖北省自然科学基金(编号:2009Chb008 2010CDB06603) 湖北省教育厅重点科研项目(编号:D20101703)资助
关键词 场景分割 多模态 竞争力 时序关联共生特性 scene segmentation multi-modality force competition temporal associated co-occurrence(TAC)
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参考文献9

  • 1图像与视频检索新发展与急需解决的科学问题[J].国际学术动态,2011(2):33-38. 被引量:2
  • 2Stephen W.Smoliar,Zhang HJ.Content based video indexing and retrieval[J].IEEE Trans.on Multimedia,1994,1 (2):62-72.
  • 3Rasheed Z,Shah M.Detection and representation of scenes in videos[J].IEEE Trans.on Multimedia,2005,7(6):1097-1105.
  • 4Fei Wu,Yanan Liu,Yueting Zhuang.Tensor-based transductive learning for multi-modality video semantic concept detection[J].IEEE Transactions on Multimedia,2009,11 (5):868-878.
  • 5Yanlan Liu,Fei Wu.Video semantic concepet detection using multi-modality subspace correlation propagation[C] //Proc.of the 13th Int'l Multimedia Modeling Conference,Berlin:Springer,2007:527-534.
  • 6张鸿,吴飞,庄越挺,陈建勋.一种基于内容相关性的跨媒体检索方法[J].计算机学报,2008,31(5):820-826. 被引量:34
  • 7Tong Lin,Hong Zhang.Video scene extraction by force competition[J].Proceeding of ICME Conf,Tokyo,2001:753-756.
  • 8S.F.Chang,W.Chen,H.J.Meng.VideoQ:An automated content-based video search system using vis ual cues[C] //Proc.of the 5th ACM Multimedia 97.Seattle,USA,1997:313-324.
  • 9Dimitrova N,Zhang H J,Shahraray B,et al.Applications of video content analysis and retrieval[J].IEEE Multimedia,2002,9 (3):42-55.

二级参考文献15

  • 1Zhang Hong-Jiang, Zhong Di. Schema for visual featurebased image indexing Proceedings of the SPIE, Storage and Retrieval for Image and Video Database. San Diego, USA, 1995:36-46.
  • 2David R H, John S T. KCCA for different level precision in content-based image retrieval Proceedings of the 3rd International Workshop on Content-Based Multimedia Indexing. Rennes, France, 2003:51-56.
  • 3Snoek C G M, Worring M, Geusebroek J M. Semantic video search engine Proceedings of the TRECVID Workshop. Gaithersburg, USA, 2004:102-105.
  • 4Zhao Xue-Yan, Zhuang Yue-Ting, Wu Fei. Audio clip retrieval with fast relevance feedback based on constrained fuzzy clustering and stored Index table Proceedings of the Pacific-Rim Conference on Multimedia. Taiwan, China, 2002:237-244.
  • 5McGurk J M. Hearing lips and seeing voices. Nature, 1976, 264(5588) : 746-748.
  • 6Hardoon D R. A correlation approach for automatic image annotation Proceedings of the 2nd International Conference on Advanced Data Mining and Applications. Xi'an, China, 2006:681-692.
  • 7Wang Xin-Jing, Ma Wei-Ying, Xue Gui-Rong, Li Xing. Multi-model similarity propagation and its application for web image retrieval Proceedings of the ACM Multimedia Conference. New York, USA, 2004:944-951.
  • 8Ma Qiang, Akiyo Nadamoto, Katsumi Tanaka. Complementary information retrieval for cross-media news content. Proceedings of Information Systems, 2006, 31 (7): 659-678.
  • 9Adams W H, Iyengar G, Lin C Y. Semantic indexing of multimedia content using visual, audio and text cues. Eurasip Journal on Applied Signal Processing, 2003(2) : 170-185.
  • 10Joliffe I T. Principal Component Analysis. New York: Springer-Verlag, 1986:74-81.

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