Crowd-Sourced Procedural Animation Optimisation: Comparing Desktop and VR Behaviour

Abstract

Procedural animation systems are capable of synthesising life-like organic motion automatically. However due to extensive parameterisation, tuning these systems can be very difficult. Not only are there potentially hundreds of interlinked parameters, the resultant animation can be very subjective and the process is difficult to automate effectively.In this paper we describe a crowd-sourced approach to procedural animation parameter optimisation using genetic algorithms. We test our approach by asking users to interactively rate a population of virtual dolphins to a prescribed behavioural criteria. Our results show that within a few generations a group of users can successfully tune the system toward a desired behaviour.Our secondary motivation is to investigate if there are differences in animation and behavioural preference between observations made using a standard desktop monitor and those made using Virtual Reality (VR). We describe a study where users tuned two sets of dolphin animation systems in parallel, one using a normal monitor and another using an Oculus Rift. Our results indicate that being immersed in VR leads to some key differences in preferred behaviour.