  The production of animation is a resource intensive process in game
companies. Therefore, techniques to synthesize animations have been developed.
However, these procedural techniques offer limited adaptability by animation
artists. In order to solve this, a fuzzy neural network model of the animation
is proposed, where the parameters can be tuned either by machine learning
techniques that use motion capture data as training data or by the animation
artist himself. This paper illustrates how this real time procedural animation
system can be developed, taking the human gait on flat terrain and inclined
surfaces as example. Currently, the parametric model is capable of synthesizing
animations for various limb sizes and step sizes.
