Leveraging visual concepts and query performance prediction for semantic-theme-based video retrieval

@article{Rudinac2012LeveragingVC,
  title={Leveraging visual concepts and query performance prediction for semantic-theme-based video retrieval},
  author={Stevan Rudinac and Martha Larson and Alan Hanjalic},
  journal={International Journal of Multimedia Information Retrieval},
  year={2012},
  volume={1},
  pages={263-280}
}
In this paper, we present a novel approach that utilizes noisy shot-level visual concept detection to improve text-based video retrieval. As opposed to most of the related work in the field, we consider entire videos as the retrieval units and focus on queries that address a general subject matter (semantic theme) of a video. Retrieval is performed using a coherence-based query performance prediction framework. In this framework, we make use of video representations derived from the visual… CONTINUE READING
Highly Cited
This paper has 21 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 12 citations

References

Publications referenced by this paper.
Showing 1-10 of 31 references

CU- VIREO374: Fusing Columbia374 and VIREO374 for Large Scale Semantic Concept Detection

  • YG Jiang, A Yanagawa, SF Chang, CW Ngo
  • ADVENT Technical Report
  • 2008
Highly Influential
4 Excerpts