Improving the recognition of interleaved activities

  • Authors:
  • Joseph Modayil;Tongxin Bai;Henry Kautz

  • Affiliations:
  • University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY

  • Venue:
  • UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
  • Year:
  • 2008

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Abstract

We introduce Interleaved Hidden Markov Models for recognizing multitasked activities. The model captures both inter-activity and intra-activity dynamics. Although the state space is intractably large, we describe an approximation that is both effective and efficient. This method significantly reduces the error rate when compared with previously proposed methods. The algorithm is suitable for mobile platforms where computational resources may be limited.