Trajectory synthesis by hierarchical spatio-temporal correspondence: comparison of different methods

  • Authors:
  • Johannes Mezger;Winfried Ilg;Martin A. Giese

  • Affiliations:
  • University of Tübingen, Germany;Hertie Inst. for Clinical Brain Research, Tübingen, Germany;Hertie Inst. for Clinical Brain Research, Tübingen, Germany

  • Venue:
  • APGV '05 Proceedings of the 2nd symposium on Applied perception in graphics and visualization
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present several methods for the generation of complex human motion trajectories by linear combination of prototypical example trajectories with well-defined styles. These methods decompose longer trajectories automatically into movement primitives by robust matching with stored templates. To synthesize movement primitives with new style properties, segments from the prototype trajectories are linearly combined. These linear combinations are based on the computation of spatio-temporal correspondence between trajectory segments. The synthesized new movement primitives are automatically concatenated into longer action sequences, trying to minimize artifacts at the transition points. The proposed methods are evaluated by synthesizing movement sequences from martial arts ("karate katas") that include movements primitives with different styles. For assessing the physical correctness of the generated movements we employ a zero-moment-point criterion. This physical measure was very similar for real human movement trajectories and trajectories synthesized by linear combination. In addition, we evaluated the perceptual quality of the synthesized movement sequences in a psychophysical study, involving naive subjects and computer graphics experts. We found significant differences between the different methods. For complex movements methods based on space-time correspondence seem to outperform algorithms without time-warping. In addition, computer graphics experts seem to be more sensitive to artifacts in the trajectories than normal observers.