Investigating perceptually based models to predict importance of facial blendshapes
Citation:
Emma Carrigan, Katja Zibrek, Rozenn Dahyot, Rachel McDonnell, Investigating perceptually based models to predict importance of facial blendshapes, Proceedings - MIG 2020: 13th ACM SIGGRAPH Conference on Motion, Interaction, and Games, ACM SIGGRAPH Conference on Motion, Interaction and Games, 2020, 2020Download Item:
Abstract:
Blendshape facial rigs are used extensively in the industry for facial animation of virtual humans. However, storing and manipulating large numbers of facial meshes is costly in terms of memory and computation for gaming applications, yet the relative perceptual importance of blendshapes has not yet been investigated. Research in Psychology and Neuroscience has shown that our brains process faces differently than other objects, so we postulate that the perception of facial expressions will be feature-dependent rather than based purely on the amount of movement required to make the expression. In this paper, we explore the noticeability of blendshapes under different activation levels, and present new perceptually based models to predict perceptual importance of blendshapes. The models predict visibility based on commonly-used geometry and image-based metrics.
Author's Homepage:
http://people.tcd.ie/ramcdonnDescription:
PUBLISHED
Author: Mc Donnell, Rachel
Other Titles:
Proceedings - MIG 2020: 13th ACM SIGGRAPH Conference on Motion, Interaction, and GamesACM SIGGRAPH Conference on Motion, Interaction and Games
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Conference PaperCollections
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Full text availableKeywords:
facial rig, facial animation of virtual humans, Action units, Perception, Linear model, BlendshapesDOI:
http://dx.doi.org/10.1145/3424636.3426904Metadata
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