Open Access Te Herenga Waka-Victoria University of Wellington
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Manifold Learning Techniques for Editing Motion Capture Data

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posted on 2021-11-16, 01:02 authored by Dean, Christopher

Streamlining the process of editing motion capture data and keyframe character animation is a fundamental problem in the animation field. This paper explores a new method for editing character animation, by using a data-driven pose distance as a falloff to interpolate new poses seamlessly into the sequence. This pose distance is the measure given by Green's function of the pose space Laplacian. The falloff shape and timing extent are naturally suited to the skeleton's range of motion, replacing the need for a manually customized falloff spline. This data-driven falloff is somewhat analogous to the difference between a generic spline and the ``magic wand'' selection in an image editor, but applied to the animation domain. It also supports powerful non-local edit propagation in which edits are applied to all similar poses in the entire animation sequence.

History

Copyright Date

2016-01-01

Date of Award

2016-01-01

Publisher

Te Herenga Waka—Victoria University of Wellington

Rights License

Author Retains Copyright

Degree Discipline

Computer Science

Degree Grantor

Te Herenga Waka—Victoria University of Wellington

Degree Level

Masters

Degree Name

Master of Science

ANZSRC Type Of Activity code

3 APPLIED RESEARCH

Victoria University of Wellington Item Type

Awarded Research Masters Thesis

Language

en_NZ

Victoria University of Wellington School

School of Engineering and Computer Science

Advisors

Lewis, John; Rhee, Taehyun