Complex Activity Recognition Using Context Driven Activity Theory in Home Environments

  • Saguna
  • Arkady Zaslavsky
  • Dipanjan Chakraborty
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6869)


This paper proposes a context driven activity theory (CDAT) and reasoning approach for recognition of concurrent and interleaved complex activities of daily living (ADL) which involves no training and minimal annotation during the setup phase. We develop and validate our CDAT using the novel complex activity recognition algorithm on two users for three weeks. The algorithm accuracy reaches 88.5% for concurrent and interleaved activities. The inferencing of complex activities is performed online and mapped onto situations in near real-time mode. The developed systems performance is analyzed and its behavior evaluated.


Activity recognition context-awareness situations 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Saguna
    • 1
    • 2
  • Arkady Zaslavsky
    • 1
    • 2
  • Dipanjan Chakraborty
    • 3
  1. 1.Monash UniversityMelbourneAustralia
  2. 2.Lulea University of TechnologyLuleaSweden
  3. 3.IBM Research, India Research LabNew DelhiIndia

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