Convex Optimization Methods for Image-based 3D Reconstruction (Prof. D. Cremers)

While traditional approaches have been focused on computing correspondence and 3D structure for a sparse set of feature points, more recent approaches aim at directly computing dense geometric surfaces using all available image data. In my talk, I will present some recent developments on convex formulations for dense reconstruction from multiple images or multiple videos. Furthermore, I will present real-time capable direct methods for reconstructing the world from handheld color or RGB-D cameras. Applications include 3D photography, free-viewpoint television and driver assistance.