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PhD Student

Dennis Burgermeister
Dennis Burgermeister, M.Sc.

Building 9
Room 132

Phone +49 7121 271 - 4010

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Dennis Burgermeister
Dennis Burgermeister, M.Sc.

Building 9 , Room 132

Phone +49 7121 271 - 4010


I am a PhD Student in the cognitive system research group. I work mainly on autonomous driving related projects. My work is focused on human related, computer-vision based algorithms. Main tasks include pedestrian detection, pose recognition, action recognition and human intention prediction. My approach is heavily simulation based, so I work with motion tracking (optical Vicon system and IMUs) data as well as 3D scanned models as data source. Data for computer vision algorithms is retrieved from self built simulations, currently based on Unity®.

Simulation Example
since 2016Researcher & PhD Student, Reutlingen University/Reutlingen Research Institute: Visual scene analysis, motion capture, human motioan simulation
2013-2016Software developer, Kratzer Automation AG: Development of (mainly battery) test field management software
2012-2013Intern/Graduating student, Airbus Group (formerly EADS): Handwriting recognition based on an optical tracking system/ Linked data driven Web3D Application in an aerospace context
2008-2013Media & Communication Computer Science (B.Sc./ M.Sc.), Reutlingen University

Ludl D., Gulde T., Curio C. (2020) Enhancing data-driven algorithms for human pose estimation and action recognition through simulation, in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2020.2988504.

[ DOI ]


Ludl D., Gulde T., Curio C. (2019) Simple yet efficient real-time pose-based action recognition, 22nd IEEE International Conference on Intelligent Transportation Systems (ITSC), 2019, pp. 581–588, doi: 10.1109/ITSC.2019.8917128.

[ DOI | Source Code ]

Gulde T., Ludl D., Andrejtschik J., Thalji S., Curio C. (2019): RoPose-Real: Real World Dataset Acquisition for Data-Driven Industrial Robot Arm Pose Estimation, 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 4389-4395, doi: 10.1109/ICRA.2019.8793900.

[ DOI ]

Essich, M., Ludl, D., Gulde, T. and Curio, C. (2019) Learning to Translate Between Real World and Simulated 3D Sensors While Transferring Task Models, 2019 International Conference on 3D Vision (3DV), Québec City, QC, Canada, 2019, pp. 681-689, doi: 10.1109/3DV.2019.00080.

[ DOI ]


Ludl D., Gulde T., Thalji S., Curio C. (2018): Using simulation to improve human pose estimation for corner cases, 21st IEEE International Conference on Intelligent Transportation Systems (ITSC), ​November 4-7, Hawaii, USA.

Runner-up Best Paper Award

[ DOI | PDF | Source Code ]

Ludl D., Leisten, D., Thalji S., Gulde T., Curio C. (2018): VR-Based Simulation Framework towards Interactive Human Activity UnderstandingIEEE ITSC2018 - Invited Workshop Talk

Gulde T., Ludl D., Curio C. (2018): RoPose: CNN-Based 2D Pose Estimation of Industrial Robots, 14th IEEE Conference on Automation Science and Engineering (CASE), Munich, August.

[ PDF ]


Ludl D., Randler D., Browatzki B., Curio C. (2016): Towards purposeful intention prediction of pedestriansIEEE IV2016 - Invited Workshop Talk


Jannasch M., Ludl D., Vöhringer C. (2012): Low-Cost NUI. Informatiktage 2012: 107-110