Neural Capture and Synthesis Article 2018

HeadOn: Real-time Reenactment of Human Portrait Videos

Thumb ticker sm justus thies
Neural Capture and Synthesis, Perceiving Systems
Max Planck Research Group Leader
Thumb  19

We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel real-time reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.

Author(s): Thies, J. and Zollhöfer, M. and Stamminger, M. and Theobalt, C. and Nießner, M.
Journal: ACM Transactions on Graphics 2018 (TOG)
Year: 2018
Bibtex Type: Article (article)
URL: https://justusthies.github.io/posts/headon/
Electronic Archiving: grant_archive
Links:

BibTex

@article{thies2018headon,
  title = {HeadOn: Real-time Reenactment of Human Portrait Videos},
  journal = {ACM Transactions on Graphics 2018 (TOG)},
  abstract = {We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel real-time reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.},
  year = {2018},
  slug = {thies2018headon},
  author = {Thies, J. and Zollh{\"o}fer, M. and Stamminger, M. and Theobalt, C. and Nie{\ss}ner, M.},
  url = {https://justusthies.github.io/posts/headon/}
}