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Extracting Activities from Multimodal Observation

  • Oliver Brdiczka
  • Jérôme Maisonnasse
  • Patrick Reignier
  • James L. Crowley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

This paper addresses the extraction of small group configurations and activities in an intelligent meeting environment. The proposed approach takes a continuous stream of observations coming from different sensors in the environment as input. The goal is to separate distinct distributions of these observations corresponding to distinct group configurations and activities. In this paper, we explore an unsupervised method based on the calculation of the Jeffrey divergence between histograms over observations. The obtained distinct distributions of observations can be interpreted as distinct segments of group configuration and activity. To evaluate this approach, we recorded a seminar and a cocktail party meeting. The observations of the seminar were generated by a speech activity detector, while the observations of the cocktail party meeting were generated by both the speech activity detector and a visual tracking system. We measured the correspondence between detected segments and labelled group configurations and activities. The obtained results are promising, in particular as our method is completely unsupervised.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Oliver Brdiczka
    • 1
  • Jérôme Maisonnasse
    • 1
  • Patrick Reignier
    • 1
  • James L. Crowley
    • 1
  1. 1.INRIA Rhône-AlpesMontbonnotFrance

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