PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Detecting F-formations as Dominant Sets
Hayley Hung and B Krose
In: ICMI '11 Proceedings of the 13th international conference on multimodal interfaces, 14 - 18 November, Alicante, Spain.

Abstract

The first step towards analysing social interactive behaviour in crowded environments is to identify who is interacting with whom. This paper presents a new method for detecting focused encounters or F-formations in a crowded, real-life social environment. An F-formation is a specific instance of a group of people who are congregated together with the intent of conversing and exchanging information with each other. We propose a new method of estimating F-formations using a graph clustering algorithm by formulating the problem in terms of identifying dominant sets. A dominant set is a form of maximal clique which occurs in edge weighted graphs. As well as using the proximity between people, body orientation information is used; we propose a socially motivated estimate of focus orientation (SMEFO), which is calculated with location information only. Our experiments show significant improvements in performance over the existing modularity cut algorithm and indicates the effectiveness of using a local social context for detecting F-formations.

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EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:9493
Deposited By:Hayley Hung
Deposited On:16 March 2012