Building new tools for synthetic image animation by using evolutionary techniques

Abstract

Particle-based models and articulated models are increasingly used in synthetic image animation applications. This paper aims at showing examples of how Evolutionary Algorithms can be used as tools to build realistic physical models for image animation. First, a method to detect regions with rigid 2D motion in image sequences, without solving explicitly the Optical Flow equation, is presented. It is based on the resolution of an equation involving rotation descriptors and first-order image derivatives. An evolutionary technique is used to obtain a raw segmentation based on motion; the result of segmentation is then refined by an accumulation technique in order to determine more accurate rotation centres and deduce articulation points. Second, an evolutionary algorithm designed to identify internal parameters of a mass-spring animation model from kinematic data (“Physics from Motion”) is presented through its application to cloth animation modelling.