TY - GEN
T1 - Photorealistic face transfer in 2D and 3D video
AU - Merget, Daniel
AU - Tiefenbacher, Philipp
AU - Babaee, Mohammadreza
AU - Mitov, Nikola
AU - Rigoll, Gerhard
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 3D face transfer has been employed in a wide field of settings such as videoconferencing, gaming, or Hollywood movie production. State-of-the-art algorithms often suffer from a high sensitivity to tracking errors, require manual post-processing, or are overly complex in terms of computation time. Addressing these issues, we propose a lightweight system which is capable to transfer facial features in both 2D and 3D. This is accomplished by finding a dense correspondence between a source and target face, and then performing Poisson cloning. We solve the correspondence problem efficiently by a sparse initial registration and a subsequent warping, which is refined in a surface matching step using topological projections. Additional processing power is saved by converting extrapolation problems to simple interpolation problems without loss of precision. The final results are photorealistic face transfers in either 2D or 3D between arbitrary facial video streams.
AB - 3D face transfer has been employed in a wide field of settings such as videoconferencing, gaming, or Hollywood movie production. State-of-the-art algorithms often suffer from a high sensitivity to tracking errors, require manual post-processing, or are overly complex in terms of computation time. Addressing these issues, we propose a lightweight system which is capable to transfer facial features in both 2D and 3D. This is accomplished by finding a dense correspondence between a source and target face, and then performing Poisson cloning. We solve the correspondence problem efficiently by a sparse initial registration and a subsequent warping, which is refined in a surface matching step using topological projections. Additional processing power is saved by converting extrapolation problems to simple interpolation problems without loss of precision. The final results are photorealistic face transfers in either 2D or 3D between arbitrary facial video streams.
UR - http://www.scopus.com/inward/record.url?scp=84952361120&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24947-6_33
DO - 10.1007/978-3-319-24947-6_33
M3 - Conference contribution
AN - SCOPUS:84952361120
SN - 9783319249469
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 400
EP - 411
BT - Pattern Recognition - 37th German Conference, GCPR 2015, Proceedings
A2 - Leibe, Bastian
A2 - Gall, Juergen
A2 - Gehler, Peter
PB - Springer Verlag
T2 - 37th German Conference on Pattern Recognition, GCPR 2015
Y2 - 7 October 2015 through 10 October 2015
ER -