DATA-DRIVEN GROUP ANIMATION
  Kuang-Yi Chen     Dobromir Todorov - Dobry     Chun-Wei Wang     Yu-Chi Lai  
Kuang-Yi Chen, Dobromir Todorov, Chun-Wei Wang, Yu-Chi Lai, DATA-DRIVEN GROUP ANIMATION, CVGIP 2012
Abstract

We introduce Data-Driven Groups (DDGs), an animation technique for groups of discrete agents, such as flocks, herds, or small crowds. DDGs are a natural  extension of human motion graphs to groups. They create motion by piecing together a sequence of recorded motion clips. The graph structure identifies
clips that can be appended while maintaining continuity  in the motion. We discuss a method for building DDGs for discrete agents and algorithms for extracting motion from the graph to meet environment constraints. The resulting animations show realistic motion at significantly reduced computational cost compared to simulation.

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