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Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning

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Location and Context Awareness (LoCA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5561))

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Abstract

Activity recognition has attracted increasing attention in recent years due to its potential to enable a number of compelling context-aware applications. As most approaches rely on supervised learning methods, obtaining substantial amounts of labeled data is often an important bottle-neck for these approaches. In this paper, we present and explore a novel method for activity recognition from sparsely labeled data. The method is based on multi-instance learning allowing to significantly reduce the required level of supervision. In particular we propose several novel extensions of multi-instance learning to support different annotation strategies. The validity of the approach is demonstrated on two public datasets for three different labeling scenarios.

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Author information

Authors and Affiliations

  1. Fraunhofer IGD, Germany

    Maja Stikic

  2. TU Darmstadt, Germany

    Bernt Schiele

Authors
  1. Maja Stikic
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  2. Bernt Schiele
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Editor information

Editors and Affiliations

  1. Computer Science Department, NH 03755, Dartmouth, Hanover, USA

    Tanzeem Choudhury

  2. Complex & Adaptive Systems Laboratory, School of Computer Science & Informatics, University College Dublin, Belfield Office Park, Dublin 4, Ireland

    Aaron Quigley

  3. Institute of Communications and Navigation, German Aerospace Center, 82234 Wessling/Oberpfaffenhofen, Germany, and Digital Enterprise Research Institute (DERI), University of Innsbruck, 6020, Innsbruck, Austria

    Thomas Strang

  4. Semiconductor Group R&D Division, Sony Corporation, 1-11-1 Osaki, Shinagawa-ku, 141-0032, Tokyo, Japan

    Koji Suginuma

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© 2009 Springer-Verlag Berlin Heidelberg

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Stikic, M., Schiele, B. (2009). Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning. In: Choudhury, T., Quigley, A., Strang, T., Suginuma, K. (eds) Location and Context Awareness. LoCA 2009. Lecture Notes in Computer Science, vol 5561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01721-6_10

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  • DOI: https://doi.org/10.1007/978-3-642-01721-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01720-9

  • Online ISBN: 978-3-642-01721-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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