Computer Science

Computer Science Colloquium

Prof. Dr. Thomas Pock
Graz University of Technology

Learning better models for computer vision

Tue 14.06.2016, 16:30, 60 minutes
Computer Science Building (SP 3), Room 048


Until recently, computational imaging, learning was seldomly used in practical applications of machine vision. Recent progress in computing power as well as new algorithmic insights makes these techniques now feasible and exploitable. According to Bayes' theorem, the posterior distribution of a certain vision problem is proportional to the product of a prior distribution and a data likelihood distribution. The classical maximum a-posterior (MAP) estimate is given by the sample that maximizes the posterior probability, or equivalently minimizes the negative logarithm of the posterior probability. This leads to the minimization of a cost function that is given by the sum of a regularization term (prior) and a data fidelity term (data likelihood). Rather than using handcrafted models for these terms, we make use of machine learning techniques to learn "better" models. In a first application we show how to learn a powerful regularization term for high-quality image reconstruction from compressed sensing MRI. Our learned algorithm allows to speed-up the MRI acquisition time by a factor 4-6. In a second application, we show how to learn the data fidelity term for a stereo algorithm. Our learned stereo algorithm yields state-of-the-art results on a variety of depth estimation benchmarks while running in real-time.


Thomas Pock, born 1978 in Graz, received his MSc (1998-2004) and his PhD (2005-2008) in Computer Engineering (Telematik) from Graz University of Technology. After a Post-doc position at the University of Bonn, he moved back to Graz University of Technology where he has been an Assistant Professor at the Institute for Computer Graphics and Vision. In 2013 Thomas Pock received the START price of the Austrian Science Fund (FWF) and the German Pattern recognition award of the German association for pattern recognition (DAGM) and in 2014, Thomas Pock received an starting grant from the European Research Council (ERC). Since June 2014, Thomas Pock is a Professor of Computer Science at Graz University of Technology (AIT Stiftungsprofessur "Mobile Computer Vision") and a principal scientist at the Department of Safety and Security at the Austrian Institute of Technology (AIT). The focus of his research is the development of mathematical models for computer vision and image processing in mobile scenarios as well as the development of efficient algorithms to compute these models.
Invited by Univ.-Prof. Dr. Oliver Bimber, Institute of Computer Graphics

The Computer Science Colloquium is organized by the Department of Coputer Science at JKU, the Österreichische Gesellschaft für Informatik (ÖGI) and the Österreichische Computergesellschaft (OCG).
List of all talks
Last modified on Thursday, 01-Jan-1970 01:00:00 CET