F-formation detection: individuating free-standing conversational groups in images

PLoS One. 2015 May 21;10(5):e0123783. doi: 10.1371/journal.pone.0123783. eCollection 2015.

Abstract

Detection of groups of interacting people is a very interesting and useful task in many modern technologies, with application fields spanning from video-surveillance to social robotics. In this paper we first furnish a rigorous definition of group considering the background of the social sciences: this allows us to specify many kinds of group, so far neglected in the Computer Vision literature. On top of this taxonomy we present a detailed state of the art on the group detection algorithms. Then, as a main contribution, we present a brand new method for the automatic detection of groups in still images, which is based on a graph-cuts framework for clustering individuals; in particular, we are able to codify in a computational sense the sociological definition of F-formation, that is very useful to encode a group having only proxemic information: position and orientation of people. We call the proposed method Graph-Cuts for F-formation (GCFF). We show how GCFF definitely outperforms all the state of the art methods in terms of different accuracy measures (some of them are brand new), demonstrating also a strong robustness to noise and versatility in recognizing groups of various cardinality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Humans
  • Interpersonal Relations*
  • Pattern Recognition, Automated / methods*
  • Photography
  • Social Behavior*

Grants and funding

F. Setti and C. Bassetti are supported by the VisCoSo project grant, financed by the Autonomous Province of Trento through the “Team 2011” funding programme (http://www.uniricerca.provincia.tn.it).