Modelling Collective Animal Behaviour using Extended Point Distribution Models

N. Sumpter , R.D. Boyle , and R.D. Tillett

School of Computer Studies, University of Leeds, LS2 9JT, UK
Silsoe Research Institute, Silsoe, Bedford MK45 4HS, UK
e-mail: neils@scs.leeds.ac.uk
homepage: http://www.scs.leeds.ac.uk/neils/

Abstract:

Models of collective animal behaviour, such as the flocking of birds, are usually based upon simulations that appear to exhibit properties of the animals in question. In this paper, we describe an alternative approach; that of automatically extracting a model of animal behaviour from video sequences of real animals.

Point distribution models (PDMs) are used to describe the shape of a flock of ducks in response to a robot predator. Additional parameters that govern this interaction are chosen and included in the model by extending the PDM. A suitable method for scaling their influence in the PDM is described. The motivation here is not in producing a PDM to assist in tracking, but one that describes the real shape behaviour of a group of animals, which may be used to measure the accuracy of simulations.

 
• 1 Introduction
• 2 Training a Standard Point Distribution Model
• 3 Extending the PDM
• 4 Scaling the Influence of Parameters
• 5 Conclusions
• 6 Acknowledgements
• References