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Editing dynamic properties of captured human motion

Authors: Zoran Popovic;

Editing dynamic properties of captured human motion

Abstract

In contrast to most physically based animation techniques that synthesize human motion from scratch, we take the approach of motion transformation as the underlying paradigm for generating computer animation. In doing so we combine the expressive richness of an input animation sequence with the controllability of space-time optimization to create a wide range of realistic character animation. The space-time dynamics formulation also allows editing of intuitive, high-level motion concepts such as the time and placement of footprints, length and mass of various extremities number of body joints and gravity. Our algorithm is well suited for the reuse of highly-detailed captured motion animation. We report application of our algorithm on two such sequences: human run and human jump. As a result, both of these sequences produced a wide range of realistic motions. We show by DOF comparison how closely the resulting motion matches the reality.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Top 10%
Top 10%
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