TY - GEN
T1 - Semantic 3D motion retargeting for facial animation
AU - Curio, Cristóbal
AU - Breidt, Martin
AU - Kleiner, Mario
AU - Vuong, Quoc C.
AU - Giese, Martin A.
AU - Bülthoff, Heinrich H.
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
KW - Facial animation
KW - Facial motion
KW - Human perception
KW - Motion retargeting
KW - Performance capture
UR - http://www.scopus.com/inward/record.url?scp=34250787450&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250787450&partnerID=8YFLogxK
U2 - 10.1145/1140491.1140508
DO - 10.1145/1140491.1140508
M3 - Conference contribution
AN - SCOPUS:34250787450
SN - 1595934294
SN - 9781595934291
T3 - Proceedings - APGV 2006: Symposium on Applied Perception in Graphics and Visualization
SP - 77
EP - 84
BT - Proceedings - APGV 2006
T2 - 3rd Symposium on Applied Perception in Graphics and Visualization, APGV 2006
Y2 - 28 July 2006 through 29 July 2006
ER -