A Data-driven Appearance Model for Human Fatigue

Abstract

Humans become visibly tired during physical activity. After a set of squats, jumping jacks or walking up a flight of stairs, individuals start to pant, sweat, loose their balance, and flush. Simulating these physiological changes due to exertion and exhaustion on an animated character greatly enhances a motion's realism. These fatigue factors depend on the mechanical, physical, and biochemical function states of the human body. The difficulty ofsimulating fatigue for character animation is due in part to the complex anatomy of the human body. We present a multi-modal capturing technique for acquiring synchronized biosignal data and motion capture data to enhance character animation. The fatigue model utilizes an anatomically derived model of the human body that includes a torso, organs, face, and rigged body. This model is then driven by biosignal output. Our animations show the wide range of exhaustion behaviors synthesized from real biological data output. We demonstrate the fatigue model by augmenting standard motion capture with exhaustion effects to produce more realistic appearance changes during three exercise examples. We compare the fatigue model with both simple procedural methods and a dense markerset data capture of exercise motions.