Thomas Heitzinger




+43 1 58801 – 193194


HE 0444

Office hours

By appointment



Thomas Heitzinger is a research assistant and PhD student at the Computer Vision Lab (CVL) at TU Wien. His research interests are 3D scene understanding and human behavior analysis using depth sensors and other non-RGB based visual sensors, as well as computer vision in the absence of strong textural information. At the moment he is working on the project KIIS which aims to support security personnel and reduce the number of safety-related incidents in Austrian prisons by using a 3D sensor to register critical movement and behavioral patterns in real time.

2019 MSc. TU Wien, Logic and Computation. Thesis title: High Accuracy Semantic Segmentation for Motor Vehicles. Thesis advisor: Martin Kampel
2018 MSc. TU Wien, Technical Mathematics. Thesis title: Complex scaling for one-dimensional resonance problems in inhomogeneous exterior domains. Thesis advisor: Lothar Nannen
2016 BSc. TU Wien, Technical Mathematics. Thesis title: Radial Perfectly Matched Layer. Thesis advisor: Lothar Nannen
  • T. Heitzinger and M. Wödlinger and D. StorkArtist-specific style transfer for deep net semantic segmentation of paintings: The value of large corpora of surrogate artworksin Electronic Imaging, 2022
  • T. Heitzinger and D. StorkImproving semantic segmentation of fine art images using photographs rendered in a style learned from artworks”in Electronic Imaging, 2022
  • T. Heitzinger and M. Kampel “A Foundation for 3D Human Behavior Detection in Privacy-Sensitive Domains”,
    in 32nd British Machine Vision Conference (BMVC), 2021
  • T. Heitzinger and M. Kampel “IPT: A Dataset for Identity Preserved Tracking in Closed Domains”, in Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, January 2021
  • T. Heitzinger and M. Kampel Highly Accurate Binary Image Segmentation for Cars”, in Proceedings of the ARW & OAGM Workshop 2020, Graz, Austria, September 2020
Awards & Achievements
  • Reigning CVL Mario Kart Champion 2022
  • Best Paper Award, ARW & OAGM Workshop 2020, September 2020