Style Invariant Locomotion Classification for Character Control

We present a real‐time system for character control that relies on the classification of locomotive actions in skeletal motion capture data. Our method is both progress dependent and style invariant. Two deep neural networks are used to correlate body shape and implicit dynamics to locomotive types...

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Veröffentlicht in:	Computer graphics forum 2019-02, Vol.38 (1), p.537-548
Hauptverfasser:	Boehs, G.E., Vieira, M.L.H.
Format:	Artikel
Sprache:	eng
Schlagworte:	animation Artificial neural networks Classification Computer graphics Computing methodologies → Computer vision ‐ Motion capture Animation ‐ Motion capture Invariants Locomotion Motion capture motion control
Online-Zugang:	Volltext
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