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Graphical Models
Article . 2002 . Peer-reviewed
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Graphical Models
Article
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Article . 2002
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DBLP
Article . 2002
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Capturing the Complexity of Hair Motion

Capturing the complexity of hair motion.
Authors: Plante, Eric; Cani, Marie-Paule; Poulin, Pierre;

Capturing the Complexity of Hair Motion

Abstract

Summary: Modeling the highly inelastic interactions inside hair, and between the hair and the character body, is a determinant feature for achieving realistic hair animation. However, the extremely large number of hair strands has so far prevented animators from handling these interactions. It is also unclear if they should be treated at the level of individual hair strands. This paper proposes an approach to handle these interactions, based on a new clustering paradigm. The high friction forces between neighboring hair strands, yielding a high motion coherence, is simulated by clustering these strands into an anisotropic viscous volume representing a hair wisp. All other interactions between hair strands are approximated at the wisp level, thanks to an anisotropic behavior that allows pairs of wisps to interpenetrate or to collide depending on their relative orientations. The wisps also offer the necessary structure to efficiently simulate the collisions with the character body. The model results in visually realistic animations, where complex wisp interactions capture both continuities and discontinuities easily observed in thick, long hair

Country
France
Keywords

collision processing, physically-based animation, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], natural phenomena, hair, physically based animation, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Machine vision and scene understanding, 620, collision detection and response, models, layered, Hair

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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!
17
Average
Top 10%
Average
Green
gold