Motion Grammars for Character Animation

Abstract

The behavioral structure of human movements is imposed by multiple sources, such as rules, regulations, choreography, habits, and emotion. Our goal is to identify the behavioral structure in a specific application domain and create a novel sequence of movements that abide by structure-building rules. To do so, we exploit the ideas from formal language, such as rewriting rules and grammar parsing, and adapted those ideas to synthesize the three-dimensional animation of multiple characters. The structured motion synthesis using motion grammars is formulated in two layers. The upper layer is a symbolic description that relates the semantics of each individual's movements and the interaction among them. The lower layer provides spatial and temporal contexts to the animation. Our multi-level MCMC (Markov Chain Monte Carlo) algorithm deals with the syntax, semantics, and spatiotemporal context of human motion to produce highly-structured, animated scenes. The power and effectiveness of motion grammars are demonstrated in animating basketball games from drawings on a tactic board. Our system allows the user to position players and draw out tactical plans, which are animated automatically in virtual environments with three-dimensional, full-body characters.