Roman Pflugfelder

Roman Pflugfelder is a Marie Curie Fellow and active researcher at the Technical University of Munich (TUM), where he is affiliated with the Chair for Computer Vision and Artificial Intelligence in the School of Computation, Information and Technology. He simultaneously holds a postdoc position at the Technion in Israel under Prof. Michael Lindenbaum and serves as a lecturer at TU Wien. Currently on leave from a Scientist position at the AIT Austrian Institute of Technology in Vienna, Pflugfelder focuses on solving occlusion challenges in machine and human vision through his Marie Curie project 'Video De-Occlusion'.

His research spans object tracking and detection, motion analysis, object recognition, and visual learning, with strong emphasis on practical applications in video surveillance systems. Pflugfelder has developed notable technologies including traffic monitoring systems based on competitive learning, the CMT tracker using consensus of parts, and indoor localization with non-overlapping security cameras. His work bridges theoretical computer vision with real-world implementation, having been deployed by governmental organizations and companies.

Analysis of his recent publications (2022-2025) reveals a consistent focus on multi-object tracking, satellite imagery analysis, and occlusion handling in visual recognition systems. His work shows progression from traditional tracking methods toward more sophisticated deep learning approaches for satellite video analysis and temporal modeling to address occlusion challenges. The publications span top-tier venues including CVPR, ICCV, ECCV, and NeurIPS, demonstrating his standing in the computer vision community.

• Marie Skłodowska-Curie Fellowship (2022)
• IEEE/CvF WACV Best Paper Prize (2014)
• Multiple reviewer awards (2016 - Journal of Image and Vision Computing, 2017 - Journal of Pattern Recognition, 2019 - CVPR)

Pflugfelder supervises Master's students at TUM and previously managed a team of six researchers at AIT, coordinating the strategic 'Mobile Vision' program. He co-initiated the VOT challenges and workshop series in 2012, contributing significantly to benchmarking in visual object tracking. His research often involves interdisciplinary collaborations across European institutions and Israel, with strong emphasis on translating theoretical advances into practical surveillance applications.

As part of the Dynamic Vision and Learning Group at TUM under Prof. Laura Leal-Taixé, Pflugfelder works within a vibrant research ecosystem focused on cutting-edge computer vision problems. His current project investigates how temporal information in video sequences can overcome limitations of single-image recognition systems, drawing inspiration from cognitive science concepts like visual persistence and anorthoscopic perception.