Real - World Visual Computing

Over the last decade, the tremendous increase in computational power of graphics hardware, in conjunction with equally improved rendering algorithms, have led to the situation today where real-time visual realism is computationally attainable on almost any PC, if only the digital models to be rendered were sufficiently detailed and realistic. With rapidly advancing rendering capabilities, the modeling process has become the limiting factor in realistic computer graphics applications. Following the traditional rendering paradigm, higher visual realism can be attained only by providing more detailed and accurate scene descriptions. However, building realistic digital scene descriptions consisting of 3D geometry and object texture, surface reflectance characteristics and scene illumination, character motion and emotion is a highly labor-intensive, tedious process. Goal of this seminar is to find new ways to overcome the looming stalemate in realistic rendering caused by traditional, time-consuming modeling. One promising alternative consists of creating digital models from real-world examples if ways can be found how to endow reconstructed models with the flexibility customary in computer graphics. The trend towards model capture from real-world examples is bolstered by new sensor technologies becoming available at mass-market prices, such as Microsoft’s Kinect and time-of-flight 2D depth imagers, or Lytro’s Light Field camera. Also, the pervasiveness of smart-phones containing camera, GPS and orientation sensors allows for developing new capturing paradigms of real-world events based on a swarm of networked smart-phones. With the advent of these exciting new acquisition technologies, investigating how to best integrate these novel capture modalities into the digital modeling pipeline or how to alter traditional modeling to make optimal use of new capture technologies, has become a top priority in visual computing research. To address these challenges, interdisciplinary approaches are called for that encompass computer graphics, computer vision, and visual media production. The overall goal of the seminar is to form a lasting, interdisciplinary research community which jointly identifies and addresses the challenges in modeling from the real world and determines which research avenues will be the most promising ones to pursue over the course of the next years. Seminar 20.–25. October, 2013 – www.dagstuhl.de/13431 1998 ACM Subject Classification I.2.10 Vision and Scene Understanding, I.3.3 Picture/Image Generation, I.3.5 Object Modeling, I.3.7 Three-Dimensional Graphics and Realism, I.4.1 Digitization and Image Capture, I.4.5 Reconstruction, I.4.8 Scene Analysis, I.4.10 Image Representation, I.4.9 Applications, I.3.1 Display devices