Face2Face: Real-Time Face Capture and Reenactment of RGB Videos
Friedrich-Alexander-Universität Erlangen-Nürnberg · Max Planck Institute for Informatics · +1 more institution
Abstract
We present a novel approach for real-time facial reenactment of a monocular target video sequence (e.g., Youtube video). The source sequence is also a monocular video stream, captured live with a commodity webcam. Our goal is to animate the facial expressions of the target video by a source actor and re-render the manipulated output video in a photo-realistic fashion. To this end, we first address the under-constrained problem of facial identity recovery from monocular video by non-rigid model-based bundling. At run time, we track facial expressions of both source and target video using a dense photometric consistency measure. Reenactment is then achieved by fast and efficient deformation transfer between…
Citation impact
- FWCI
- 58.62
- Percentile
- 100%
- References
- 41
Authors
5Topics & keywords
- Computer science
- Artificial intelligence
- Computer vision
- Monocular
- Face (sociological concept)
- RGB color model
- Video capture
- Video tracking