Teaching
I offer supervision for Bachelor’s/Master’s thesis and Praktika. I am looking for students interested in Visual Motion Analysis and Tracking, Visual Learning, Multi-View Geometry and Non-Traditional Cameras:
- Praktika/Master’s thesis: Person Detection and Data Diversity
- Praktika/Master’s thesis: Deep Visual Tracking
- Praktika/Master’s thesis: Non-Ridgid SfM for Object Tracking
Students
- Stefan Sietzen, Generative Learning Tracking, Praktika
- Manuel Danner, Cell Segmentation with the U-Net Convolutional Network, Praktika
- Julian Wagner, Detecting Moving Vehicles in Satellite Videos, Praktika
Past Students
- Georg Nebehay, A Deformable Parts Model for One-Shot Object Tracking, Doctoral thesis, 2016 – now at Locatee, Zurich
- Georg Sperl, Person Classification with Convolutional Neural Networks, Master’s thesis, 2016 – now at IST Austria
- Clemens Korner, Object Tracking using Projective Invariants, Bachelor’s thesis, 2016
- Timo Kropp, Matching Omnidirectional Images in Indoor Environments, Master’s thesis, 2013 – now at MeisterLabs, Munich
- Georg Nebehay, Robust Object Tracking Based on Tracking-Learning-Detection, Master’s thesis, 2012
- Michael Boula, Time sync. of networked cameras with non- overlapping views using TTA, Bachelor’s thesis, 2011
- Timo Kropp, Visualiserung von Trajektorien live in Microsoft Bing Maps, Bachelor’s thesis, 2009
Research
This section is under construction
Benchmarking Tracking
In 2012, I initiated the Visual Object Tracking Challenge (VOT) and since then I have been co-organising annual challenges and workshops at ICCV and ECCV with Matej Kristan, Ales Leonardis, Jiri Matas and Michael Felsberg. VOT is de facto the international community benchmark in the field of visual tracking. Important results of our work are A-R measures for quantifying short-term tracking performance in terms of accuracy and robustness and the discovery of correlation filters as superior approach for tracking. More information can be found on our webpage. VOT is also part of the benchmark initiative for all things video.
Short Bio
Roman Pflugfelder is Scientist at the AIT Austrian Institute of Technology and lecturer at TU Wien. He received in 2002 a MSc degree in informatics at TU Wien and in 2008 a PhD in telematics at the TU Graz, Austria. In 2001, he was academic visitor at the Queensland University of Technology, Australia. His research focuses on visual motion analysis, tracking and recognition applied to automated video surveillance. He aims to combine sciences and theories in novel ways to gain theoretical insights into learning and inference in complex dynamical systems and to develop practical algorithms and computing systems.
Roman contributed with more than 55 papers and patents to research fields such as camera calibration, object detection, object tracking, event recognition where he received awareness of media as well as several awards and grants for his scientific achievements. Roman is senior project leader at AIT where he has been managing cooperations among universities, companies and governmental institutions. Roman co-organised the Visual Object Tracking Challenges VOT’13-14 and VOT’16-18 and was program co-chair of AVSS’15. Currently he is steering committee member of AVSS. He is regular reviewer for major computer vision conferences and journals.
Please, see my CV and my publications for details.