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Semantic 3D motion retargeting for facial animation

Lookup NU author(s): Dr Quoc Vuong

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Abstract

We present a system for realistic facial animation that decomposes facial motion capture data into semantically meaningful motion channels based on the Facial Action Coding System. A captured performance is retargeted onto a morphable 3D face model based on a semantic correspondence between motion capture and 3D scan data. The resulting facial animation reveals a high level of realism by combining the high spatial resolution of a 3D scanner with the high temporal accuracy of motion capture data that accounts for subtle facial movements with sparse measurements. Such an animation system allows us to systematically investigate human perception of moving faces. It offers control over many aspects of the appearance of a dynamic face, while utilizing as much measured data as possible to avoid artistic biases. Using our animation system, we report results of an experiment that investigates the perceived naturalness of facial motion in a preference task. For expressions with small amounts of head motion, we find a benefit for our part-based generative animation system over an example-based approach that deforms the whole face at once.


Publication metadata

Author(s): Curio C, Breidt M, Kleiner M, Vuong QC, Giese M, Bülthoff HH

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the 3rd Symposium on Applied Perception in Graphics and Visualization

Year of Conference: 2006

Pages: 77-84

Publisher: ACM Press

URL: http://dx.doi.org/10.1145/1140491.1140508

DOI: 10.1145/1140491.1140508

Library holdings: Search Newcastle University Library for this item

ISBN: 1595934294


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