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Cited by 94Video Analysis and SummarizationAdvanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Content based video matching using spatiotemporal volumes

Open access
Basharat, Arslan, Zhai, Yun, Shah, Mubarak·2008·Computer Vision and Image Understanding
DOI 10.1016/j.cviu.2007.09.016
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Crossref · 10.1016/j.cviu.2007.09.016

Cites

2 of 2 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • None of the existing definitions addresses the retrieval of same incident videos.

    “However, there does not seem to be strong consensus among researchers about which videos are considered near-duplicate videos and none of the existing definitions addresses the retrieval of same incident videos ; in this paper, we attempt to address these issues and provide solid definitions for all types of associations between videos related to the FIVR problem.”

    From FIVR: Fine-Grained Incident Video Retrieval (2019) · cites this paper as [3]

  • There is no strong consensus among researchers about which videos are considered near-duplicate videos.

    “However, there does not seem to be strong consensus among researchers about which videos are considered near-duplicate videos and none of the existing definitions addresses the retrieval of same incident videos ; in this paper, we attempt to address these issues and provide solid definitions for all types of associations between videos related to the FIVR problem.”

    From FIVR: Fine-Grained Incident Video Retrieval (2019) · cites this paper as [3]

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 30

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  4. Carson, 2002, Blobworld: image segmentation using expectation-maximization and its application to image querying, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 1026, 10.1109/TPAMI.2002.1023800 · DOI
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  10. Hauptmann, 1997, Informedia: News-on-demand multimedia information acquisition and retrieval, Intelligent Multimedia Information Retrieval, 215
  11. S. Chang, W. Chen, H. Meng, H. Sundaram, Videoq: an automated content based video search system using visual cues, in: Proceedings of the 5th ACM International Conference on Multimedia, 1997, pp. 313–324. · DOI
  12. J. Lee, J. Oh, S. Hwang, Strg-index: spatio-temporal region graph indexing for large video databases, in: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, 2005, pp. 718–729. · DOI
  13. Dagtas, 2000, Models for motion-based video indexing and retrieval, IEEE Transactions on Image Processing, 9, 88, 10.1109/83.817601 · DOI
  14. S. Sav, N. OConnor, A. Smeaton, N. Murphy, Associating low-level features with semantic concepts using video objects and relevance feedback, in: 6th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2005), Montreux, Switzerland, 2005, pp. 13–15.
  15. A. Smeaton, H. Le Borgne, N. OConnor, T. Adamek, O. Smyth, S. De Burca, Coherent segmentation of video into syntactic regions, in: 9th Irish Machine Vision and Image Processing Conference, 2005.
  16. E. Ardizzone, M. La Cascia, D. Molinelli, Motion and color based video indexing and retrieval, in: Proceedings of the International Conference on Pattern Recognition 1996, pp. 135–139. · DOI
  17. Deng, 1998, Netra-v: toward an object-based video representation, IEEE Transactions on Circuits and Systems for Video Technology, 8, 616, 10.1109/76.718508 · DOI
  18. J. Sivic, M. Everingham, A. Zisserman, Person spotting: video shot retrieval for face sets, in: Proceedings of CIVR, July.
  19. Sivic, 2006, Object level grouping for video shots, International Journal of Computer Vision, 67, 189, 10.1007/s11263-005-4264-y · DOI
  20. Rothganger, 2007, Segmenting, modeling, and matching video clips containing multiple moving objects, IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 477, 10.1109/TPAMI.2007.57 · DOI
  21. Schaffalitzky, 2003, Automated location matching in movies, Computer Vision and Image Understanding, 92, 236, 10.1016/j.cviu.2003.06.008 · DOI
  22. Kass, 1988, Snakes: Active contour models, International Journal of Computer Vision, 1, 321, 10.1007/BF00133570 · DOI
  23. Rubner, 2000, The earth mover’s distance as a metric for image retrieval, International Journal of Computer Vision, 40, 99, 10.1023/A:1026543900054 · DOI
  24. Lazebnik, 2005, A sparse texture representation using local affine regions, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, 1265, 10.1109/TPAMI.2005.151 · DOI
  25. Zhang, 2007, Local features and kernels for classification of texture and object categories: a comprehensive study, International Journal of Computer Vision, 73, 213, 10.1007/s11263-006-9794-4 · DOI
  26. Hitchcock, 1941, The distribution of a product from several sources to numerous localities, Journal of Mathematical Physics, 20, 224, 10.1002/sapm1941201224 · DOI
  27. R. Meir, G. Ratsch, An introduction to boosting and leveraging: advanced Lectures on Machine Learning, LNCS, 2003, pp. 119–184. · DOI
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  30. Comaniciu, 2002, Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 603, 10.1109/34.1000236 · DOI

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Metadata

Authors
Basharat, A., Zhai, Y., & Shah, M.
Affiliations
University of Central Florida (US)
Corresponding author
Basharat, Arslan
ORCID
Venue
Computer Vision and Image Understanding
Publisher
Elsevier BV
Published
2008-06
Volume
110
Issue
3
Pages
360-377
ISSN
1077-3142 (ISSN-L)
DOI
10.1016/j.cviu.2007.09.016
OpenAlex
W1996135397
Cited by
94
References
2
Citations by year
2026: 1 · 2025: 3 · 2024: 3 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 5 · 2018: 4 · 2017: 2 · 2016: 1 · 2015: 7 · 2014: 9 · 2013: 7 · 2012: 8
FWCI
11.37
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Computer Vision and Image Understanding (publishedVersion)
  • Journal of International Crisis and Risk Communication Research (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Analysis and Summarization
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
Keywords
video matching, video retrieval, spatio-temporal segmentation, SIFT, temporal correspondence, Wasserstein distance, bipartite matching, region splitting and merging

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