Analyzing human interactions with a network of dynamic probabilistic models

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a novel method for analyzing human interactions based on the walking trajectories of human subjects. Our principal assumption is that an interaction episode is composed of meaningful smaller unit interactions, which we call 'sub-interactions.' The whole interaction is represented by an ordered concatenation or a network of sub-interaction models. From the experiments, we could confirm the effectiveness and robustness of the proposed method by analyzing the internal work of an interaction network and comparing the performance with other previous approaches.

Original languageEnglish
Title of host publication2009 Workshop on Applications of Computer Vision, WACV 2009
DOIs
Publication statusPublished - 2009
Event2009 Workshop on Applications of Computer Vision, WACV 2009 - Snowbird, UT, United States
Duration: 2009 Dec 72009 Dec 8

Publication series

Name2009 Workshop on Applications of Computer Vision, WACV 2009

Other

Other2009 Workshop on Applications of Computer Vision, WACV 2009
CountryUnited States
CitySnowbird, UT
Period09/12/709/12/8

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Suk, H. I., Sin, B. K., & Lee, S. W. (2009). Analyzing human interactions with a network of dynamic probabilistic models. In 2009 Workshop on Applications of Computer Vision, WACV 2009 [5403108] (2009 Workshop on Applications of Computer Vision, WACV 2009). https://doi.org/10.1109/WACV.2009.5403108