Interrelation analysis for Interpersonal Behaviour understanding in social context

Kamrad Khoshhal Roudposhti, Jorge Dias

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this paper we study a probabilistic approach to characterize Interpersonal Behaviours (IBs) in a social concept by exploring the existent interrelation between body motion features. Human activities were explored in different level of complexities, such as social-based human activity. To bridge the existent big gap between human body motions and the IBs analysis, a set of proper dependencies definition between the features is vital. Inspired in the works of Alex Pentland and Rudolph Laban, we proposed a couple of layers of analysis. In the first layer, we analyse human body parts motions based on a known body motion descriptor, Laban Movement analysis (LMA). LMA composes a set of components which provides different types of human movement features. We investigated the interrelation between those LMA features of a couple of persons to provide a proper model to estimate the IBs in the second layer. To reach the goal, LMA components are used as body motion features. To computerize the model, Dynamic Bayesian Network (DBN) approach is used, because of its exibility in development and implementation of the dependencies and interrelations. The results show the importance of the interrelations to have more accurate results of the IBs estimations.

Original languageBritish English
Title of host publicationSYROCO 2012 Preprints - 10th IFAC Symposium on Robot Control
Number of pages6
StatePublished - 2012
Event10th IFAC Symposium on Robot Control, SYROCO 2012 - Dubrovnik, Croatia
Duration: 5 Sep 20127 Sep 2012

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
ISSN (Print)1474-6670


Conference10th IFAC Symposium on Robot Control, SYROCO 2012


  • Bayesian approach
  • Interpersonal Behaviour analysis
  • Interrelation analysis
  • Laban movement analysis
  • Social signals


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