Computational Intelligence

Volume 343 of the series Studies in Computational Intelligence pp 135-149

Interactive Evolution for Designing Motion Variants

  • Jonathan EisenmannAffiliated withComputer Science & Engineering, The Ohio State University
  • , Matthew LewisAffiliated withAdvanced Computing Center for the Arts & Design, The Ohio State University
  • , Bryan ClineAffiliated withComputer Science & Engineering, The Ohio State University

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We present an intuitive method for novice users to interactively design custom populations of stylized, heterogeneous motion, from one input motion. The user sets up lattice deformers which are used by a genetic algorithm to manipulate the animation channels of the input motion and create new motion variants. Our interactive evolutionary design environment allows the user to traverse the available space of possibilities, presents the user with populations of motion, and gradually converges to a satisfactory set of solutions. Each generated motion can undergo a filtering process subject to user-specified, high-level metrics to produce a result crafted to fit the designer’s interest. We demonstrate application to both character animation and particle systems.


Evolutionary design Animation Interaction techniques Crowds Particle systems