Multi-person interaction and activity analysis: a synergistic track- and body-level analysis framework

  • Authors:

  • Sangho Park;Mohan M. Trivedi

  • Affiliations:

  • University of California at San Diego, Computer Vision and Robotics Research Laboratory, 92093-0434, La Jolla, CA, USA;University of California at San Diego, Computer Vision and Robotics Research Laboratory, 92093-0434, La Jolla, CA, USA

  • Venue:
  • Machine Vision and Applications
  • Year:
  • 2007

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Abstract

This paper presents a synergistic track- and body-level analysis framework for multi-person interaction and activity analysis in the context of video surveillance. The proposed two-level analysis framework covers human activities both in wide and narrow fields of view with distributed camera sensors. The track-level analysis deals with the gross-level activity patterns of multiple tracks in various wide-area surveillance situations. The body-level analysis focuses on detailed-level activity patterns of individuals in isolation or in groups. ‘Spatio-temporal personal space’ is introduced to model various patterns of grouping behavior between persons. ‘Adaptive context switching’ is proposed to mediate the track-level and body-level analysis depending on the interpersonal configuration and imaging fidelity. Our approach is based on the hierarchy of action concepts: static pose, dynamic gesture, body-part action, single-person activity, and group interaction. Event ontology with human activity hierarchy combines the multi-level analysis results to form a semantically meaningful event description. Experimental results with real-world data show the effectiveness of the proposed framework.