Official music video "Who Cares" by Symbiz Sound; the first major production using our Virtual Video Camera.
Dubstep, spray cans, brush and paint join forces and unite with the latest digital production techniques. All imagery depicts live action graffiti and performance. Camera motion added in post production using the Virtual Video Camera.
A Framework for Image-Based Stereoscopic View Synthesis from Asynchronous Multi-View Data
in Emerging Technologies for 3D Video: Creation, Coding, Transmission and Rendering, Wiley, ISBN 978-1-118-35511-4, pp. 249-270, May 2013.
Making of ”Who Cares?” HD Stereoscopic Free Viewpoint Video
in Proc. European Conference on Visual Media Production (CVMP), vol. 8, pp. 1-10, November 2011.
Flowlab - an interactive tool for editing dense image correspondences
in Proc. European Conference on Visual Media Production (CVMP), August 2011.
The goal of this project is to develop algorithms in image space that allow photo-realistic editing of dynamic 3D scenes. Traditional 2D editing tools cannot be applied to 3D video as in addition to correspondences in time spatial correspondences are needed for consistent editing. In this project we analyze how to make use of the redundancy in multi-stereoscopic videos to compute robust and dense correspondence fields. these space-time correspondences can then be used to propagate changes applied to one frame consistently to all other frames in the video. Beside the transition of classical video editing tools we want to develop new tools specifically for 3D video content.
This project has been funded by ERC Grant #256941 `Reality CG` and the German Science Foundation, DFG MA2555/4-2.
Scope of "Reality CG" is to pioneer a novel approach to modelling, editing and rendering in computer graphics. Instead of manually creating digital models of virtual worlds, Reality CG will explore new ways to achieve visual realism from the kind of approximate models that can be derived from conventional, real-world imagery as input.
Goal of this project is to assess the quality of rendered videos and especially detect those frames that contain visible artifacts, e.g. ghosting, blurring or popping.
The Virtual Video Camera research project is aimed to provide algorithms for rendering free-viewpoint video from asynchronous camcorder captures. We want to record our multi-video data without the need of specialized hardware or intrusive setup procedures (e.g., waving calibration patterns).