Real-time Face Capture and Reenactment of RGB Videos


Published on Mar 17, 2016 by Matthias Niessner

CVPR 2016 Paper Video (Oral)
Project Page: http://www.graphics.stanford.edu/~nie…

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 source and target. The mouth interior that best matches the re-targeted expression is retrieved from the target sequence and warped to produce an accurate fit. Finally, we convincingly re-render the synthesized target face on top of the corresponding video stream such that it seamlessly blends with the real-world illumination. We demonstrate our method in a live setup, where Youtube videos are reenacted in real time.

One thought on “Real-time Face Capture and Reenactment of RGB Videos

  1. So, you cannot really believe any interview you see from here on out. They can “fake it” anytime they please and put words in GWB’s mouth that even he couldn’t pronounce. They can do it with anyone. It’s all theater anyway so what’s the difference?

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