Learning spatio-temporal patterns for predicting object behaviour

Rule-based systems employed to model complex object behaviours, do not necessarily provide a realistic portrayal of true behaviour. To capture the real characteristics in a specific environment, a better model may be learnt from observation. This paper presents a novel approach to learning longterm spatio-temporal patterns of objects in image sequences, using a neural network paradigm to predict future behaviour. The results demonstrate the application of our approach to the problem of predicting animal behaviour in response to a predator.

• Type: Journal
• Year: 2000
• Where: IVC
• Authors: Neil Sumpter, Andrew J. Bulpitt
• Keywords: Complex Object Behaviours, IVC 2000, Longterm Spatio-temporal Patterns, True Behaviour