Real-time animation of human characters with fuzzy controllers
  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. 
Koen Samyn, Sofie Van Hoecke, Bart Pieters, Charles Hollemeersch,   Aljosha Demeulemeester and Rik van de Walle
cs.GR