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VERGE in VBS 2017

Part of the Lecture Notes in Computer Science book series (LNISA,volume 10133)

Abstract

This paper presents VERGE interactive video retrieval engine, which is capable of browsing and searching into video content. The system integrates several content-based analysis and retrieval modules including concept detection, clustering, visual similarity search, object-based search, query analysis and multimodal and temporal fusion.

Keywords

  • Convolutional Neural Network
  • Video Retrieval
  • Video Shot
  • Original Query
  • Temporal Fusion

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    http://mklab-services.iti.gr/vss2016.

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Acknowledgements

This work was supported by the EU’s Horizon 2020 research and innovation programme under grant agreements H2020-687786 InVID, H2020-693092 MOVING, H2020-645012 KRISTINA and H2020-700024 TENSOR.

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Correspondence to Anastasia Moumtzidou .

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Moumtzidou, A. et al. (2017). VERGE in VBS 2017. In: Amsaleg, L., Guðmundsson, G., Gurrin, C., Jónsson, B., Satoh, S. (eds) MultiMedia Modeling. MMM 2017. Lecture Notes in Computer Science(), vol 10133. Springer, Cham. https://doi.org/10.1007/978-3-319-51814-5_46

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  • DOI: https://doi.org/10.1007/978-3-319-51814-5_46

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