Challenges in Image-Based 3D Reconstructions
Roland Angst
(Stanford Univeristy)
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Date: March 11, 2015
Description:
Driven by the needs for various applications such as robotics, immersive augmented and virtual reality, digitization of archeological sites and landmarks, medical imaging, etc., the extraction of 3D geometry from images has become increasingly important in the last couple of years. The theory of multiple view geometry which relates images from different viewpoints dates back more than 100 years. However, in practice, e.g. due to imperfections of cameras or measuring noise, the required assumptions for this theory are often not met exactly which makes 3D computer vision inherently difficult.
In my talk, I will first outline some of the challenges we are faced with and in the second part, I will focus on two of those challenges. Specifically, we will look into radial distortion estimation without calibration targets and dense 3D reconstructions for scenes where the rigidity assumption is violated. We will see how simple and very intuitive reasoning in geometric terms can provide the foundation for algorithms to tackle those challenges.
Further Information:
Roland Angst is currently affiliated to the Max Planck Center for Visual Computing and Communication. As such, he is currently a visiting assistant professor at Stanford University, where he is a member of Prof. Bernd Girod’s Image, Video, and Group as well as of Prof. Leonidas J. Guibas’ Geometric Computation Group. He will join the Max Planck Institute in Saarbrücken in April 2015.
Roland received his PhD degree from the Swiss Federal Institute of Technology (ETH) Zürich in 2012 under the supervision of Prof. Marc Pollefeys. His research focused on geometric computer vision and on subspace models and algorithms in particular. In 2010, he has received a prestigious Google European Doctoral Fellowship in Computer Vision. Roland received his Master’s degree in computer science with distinction from ETH Zürich in October 2007. His current primary research interests span computer vision and geometry, augmented and virtual reality
Created: Thursday, March 12th, 2015