期刊文献+

A comprehensive review of significant researches on content based indexing and retrieval of visual information 被引量:3

A comprehensive review of significant researches on content based indexing and retrieval of visual information
原文传递
导出
摘要 Developments in multimedia technologies have paved way for the storage of huge collections of video doc- uments on computer systems. It is essential to design tools for content-based access to the documents, so as to allow an efficient exploitation of these collections. Content based anal- ysis provides a flexible and powerful way to access video data when compared with the other traditional video analysis tech- niques. The area of content based video indexing and retrieval (CBVIR), focusing on automating the indexing, retrieval and management of video, has attracted extensive research in the last decade. CBVIR is a lively area of research with endur- ing acknowledgments from several domains. Herein a vital assessment of contemporary researches associated with the content-based indexing and retrieval of visual information. In this paper, we present an extensive review of significant researches on CBV1R. Concise description of content based video analysis along with the techniques associated with the content based video indexing and retrieval is presented. Developments in multimedia technologies have paved way for the storage of huge collections of video doc- uments on computer systems. It is essential to design tools for content-based access to the documents, so as to allow an efficient exploitation of these collections. Content based anal- ysis provides a flexible and powerful way to access video data when compared with the other traditional video analysis tech- niques. The area of content based video indexing and retrieval (CBVIR), focusing on automating the indexing, retrieval and management of video, has attracted extensive research in the last decade. CBVIR is a lively area of research with endur- ing acknowledgments from several domains. Herein a vital assessment of contemporary researches associated with the content-based indexing and retrieval of visual information. In this paper, we present an extensive review of significant researches on CBV1R. Concise description of content based video analysis along with the techniques associated with the content based video indexing and retrieval is presented.
出处 《Frontiers of Computer Science》 SCIE EI CSCD 2013年第5期782-799,共18页 中国计算机科学前沿(英文版)
关键词 nultimedia information content based video retrieval (CBVR) content based video indexing and retrieval (CBVIR) shot segmentation object segmentation feature extraction INDEXING motion estimation QUERYING key frame RETRIEVAL and indexing. nultimedia information, content based video retrieval (CBVR), content based video indexing and retrieval (CBVIR), shot segmentation, object segmentation, feature extraction, indexing, motion estimation, querying, key frame, retrieval, and indexing.
  • 相关文献

参考文献90

  • 1Hanis A, Sziranyi T, Measuring the motion similarity in video index- ing. In: Proceedings of the 4th EURASIP Conference Focused on Video/Image Processing and Multimedia Communications. 2003, 507- 512.
  • 2Calic J, Izuierdo E. Etficient key-frame extraction and video analysis. In: Proceedings of the 2002 International Conference on Information Technology: Coding and Computing. 2002, 28-33.
  • 3Carbonaro A. Ontology-based video retrieval in a semantic-based learning environment. Journal of e-Learning and Knowledge Society, 2009, 4(3): 203-212.
  • 4George A, Rajakumar B, Suresh B. Markov random field based image restoration with aid of local and global features. International Journal of Computer Applications, 2012, 48(8): 23-28.
  • 5Kundra E H, Verma E M, Aashima E. Filter for removal of impulse noise by using fuzzy logic. International Journal of Image Processing (IJIP), 2011, 3(5): 195-202.
  • 6Umamakeswari A, Rajaraman A. Object based video analysis, interpre- tation and tracking. Journal of Computer Science, 2007, 3(10): 818- 822.
  • 7Amd erescriptionA ." Object-baseTe dchnical ReportVi,de~ retrieu Valniversity du Qu6beb c,ased on motiln999analysis and.
  • 8Javed O, Shah M, Cornaniciu D. A probabilistic framework for object recognition in video. In: Proceedings of the 2004 International Confer- ence on Image Processing. 2004, 2713-2716.
  • 9Radhakrishnan R, Divakaran A, Xiong Z, Otsuka I. A content-adaptive analysis and representation framework for audio event discovery from unscripted multimedia. EURASIP Journal on Applied Signal Process- ing, 2006:1-24.
  • 10Schnettler B, Raab J. Interpretative visual analysis developments:state of the art and pending problems. Historical Social Re- search/Historische Sozialforschung, 2009, 265-295.

同被引文献9

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部