Systematic evaluation of spatio-temporal features on comparative video challenges

  • Authors:

  • Julian Stöttinger;Bogdan Tudor Goras;Thomas Pöntiz;Allan Hanbury;Nicu Sebe;Theo Gevers

  • Affiliations:

  • CVL, Institute for Computer-Aided automation, TU Vienna and CogVis Ltd., Vienna;Faculty of Electronics, Telecommuniction and Informatics, Tech. University of Iasi;CogVis Ltd., Vienna;IR Facility, Vienna;Dept. of Information Eng. and Computer Science, University of Trento;Faculty of Science, University of Amsterdam

  • Venue:
  • ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
  • Year:
  • 2010

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Abstract

In the last decade, we observed a great interest in evaluation of local visual features in the domain of images. The aim is to provide researchers guidance when selecting the best approaches for new applications and data-sets. Most of the state-of-the-art features have been extended to the temporal domain to allow for video retrieval and categorization using similar techniques to those used for images. However, there is no comprehensive evaluation of these. We provide the first comparative evaluation based on isolated and well defined alterations of video data. We select the three most promising approaches, namely the Harris3D, Hessian3D, and Gabor detectors and the HOG/HOF, SURF3D, and HOG3D descriptors. For the evaluation of the detectors, we measure their repeatability on the challenges treating the videos as 3D volumes. To evaluate the robustness of spatio-temporal descriptors, we propose a principled classification pipeline where the increasingly altered videos build a set of queries. This allows for an in-depth analysis of local detectors and descriptors and their combinations.