High-Quality Reconstruction of Static and Dynamic 3D Scenes

23. Oktober 2009


In this talk I will give an overview of some of our latest research in the field of 3D scene reconstruction. The first part of the talk focuses on new performance capture approaches for high-quality dynamic scene capture. Our algorithms enable us to jointly reconstruct detailed dynamic scene geometry as well as dynamic texture information of a moving person from only a handful of multi-view video recordings. Our methods succeed without artificial optical markers in the scene and enable us to reconstruct detailed spatio-temporally coherent geometry of human subjects in wide everyday apparel, such as a skirt or a dress. It is also feasible to capture animation models of animals. We are therefore able to exceed the application range of previous marker-based and marker-less optical motion capture approaches. In the second part of the talk I will tap on some of our recent work on static and dynamic scene capture with active time-of-flight (ToF) 3D cameras. ToF cameras enable 3D scene capture at video rate and usually also produce good data on scenes where a passive approach, like stereo, would fail. However, current ToF cameras exhibit a non- trivial noise characteristics and only provide very limit X/Y resolution. I will show how detailed 3D models of scenes can be captured despite this at a first glance obstructive characteristics of the sensor.

Short BIO:

Christian Theobalt is the head of the research group "3D Video and Vision-based Graphics" at MPI Informatik and the Max-Planck-Center for Visual Computing and Communication, Saarbruecken, Germany. From 2007 until 2009 he was a visiting assistant professor in the Department of Computer Science at Stanford University. He received his MSc degree in Artificial Intelligence from the University of Edinburgh, Scotland, and his Diplom (MS) degree in Computer Science from Saarland University, Saarbruecken, Germany, in 2000 and 2001, respectively. From 2001 to 2005 he was a researcher and PhD candidate in Hans-Peter Seidel's Computer Graphics group at MPI Informatik. In 2005, he received his PhD (Dr.-Ing.) from Saarland University and MPI. His research interests include 3D video and dynamic scene reconstruction, marker-less optical motion capture, 3D computer vision, machine learning for graphics and vision, as well as image- and physics-based rendering. In 2007, he was awarded the Otto Hahn Medal of the Max Planck Society, and in 2009 he received the EUROGRAPHICS Young Researcher Award.