Crowdsourcing Visual Detectors for Video Search B. Freiburg, J. Kamps, C. G. M. Snoek In ACM International Conference on Multimedia 2011. [bibtex] [pdf] [url]

In this paper we study social tagging at the video fragment-level using a combination of automated content understanding and the wisdom of the crowds. We are interested in the question whether crowdsourcing can be beneficial to a video search engine that automatically recognizes video fragments on a semantic level. To answer this question, we perform a 3-month online field study with a concert video search engine targeted at a dedicated user community of pop concert enthusiasts. We harvest the feedback of more than 500 active users and perform two experiments. In experiment 1 we measure user incentive to provide feedback, in experiment 2 we study the tradeoff between feedback quality and quantity when aggregated over multiple users. Results show that users provide sufficient feedback, which becomes highly reliable when a crowd agreement of 67% is enforced.



Crowdsourcing Rock N' Roll Multimedia Retrieval by Cees G. M. Snoek, B. Freiburg, J. Oomen, Roeland Ordelman. In ACM International Conference on Multimedia, 2010.

@InProceedings{FreiburgICM2011,
  author       = "Freiburg, B. and Kamps, J. and Snoek, C. G. M.",
  title        = "Crowdsourcing Visual Detectors for Video Search",
  booktitle    = "ACM International Conference on Multimedia",
  pages        = "913--916",
  year         = "2011",
  url          = "https://ivi.fnwi.uva.nl/isis/publications/2011/FreiburgICM2011",
  pdf          = "https://ivi.fnwi.uva.nl/isis/publications/2011/FreiburgICM2011/FreiburgICM2011.pdf",
  has_image    = 1
}