Profile
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M.Sc. Stephanie Käs |
My current research centers on Human Pose Estimation (HPE), especially gesture and action recognition using CNN-based methods as well as Video Language Models on fisheye images and videos. In my previous works, I contributed to data science projects in particle physics and railway engineering. I have gained significant teaching experience and place strong emphasis on clear science communication, as well as agile project and group management.
!!! Next HiWi/thesis projects will be offered in September 2025 !!!
Publications
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Käs, S., Burenko, A., Markert, L. et al.: How do Foundation Models Compare to Skeleton-Based Approaches for Gesture Recognition in Human-Robot Interaction? In Proceedings of the IEEE International Conference on Robot & Human Interactive Communication (2025).
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Käs, S., Peter, S., Thillmann, H. et al.: Systematic Evaluation of Different Projection Methods for Monocular 3D Human Pose Estimation on Heavily Distorted Fisheye Images. In Proceedings of the IEEE International Conference on Robotics and Automation (2025).
- Dort, K., Bilk, J., Käs, S. et al.: Comparison of supervised and unsupervised anomaly detection in Belle II pixel detector data. Eur. Phys. J. C 82, 587 (2022).
Student Supervision
- O. Culha, A. Weissberg: Current Student Assistants
- M. Flaig: Towards fine-grained Motion Recognition (Ongoing)
- B. Thal: Visual Anonymization in Human Body Recognition (Ongoing)
- E. Schönherr: "Evaluating Anatomical Realism in AI-Generated Human Images" (M. Sc. Thesis, Ongoing)
- L. Markert: "Gesture Recognition Using a Video Foundation Model" (B. Sc. Thesis, 09/24-03/25)
- S. Peter: Research internship on Fisheye HPE (11/23-10/24)
- H. Thillmann: "Re-Engineering an Absolute Pose Estimation Architecture: Enabling Extensibility via Modularization" (M. Sc. Thesis, 09/23-10/24)
- A. Burenko: "Stabilization, Tracking, and Gesture Recognition Methods within Skeleton-based Human Pose Estimation Framework" (M. Sc. Thesis, 09/23-09/24)
- V. Hilla: "An Analysis of Error Sources to Improve Temporal Consistency in 3D Human Pose Estimation" (M. Sc. Thesis, 09/23-07/24)
- T. Schellhaas: "Identifizierung von langsamen Pionen durch Support Vector Machines" (B. Sc. Thesis)
- Project Leader: "Stratospheric Balloon Research Project" "StratoGI" (JLU Gießen)
Teaching & Speaking Experience
Public Speaker:
- Student Hybrid Rocket Team: "HybridLaunch"
Guest Speaker:
- HASCO Summer School
- ErUM-Data-Hub
Teaching Assistant:
- Machine Learning and Computer Vision (RWTH Aachen)
- Proseminar Historical Milestones of Machine Learning (RWTH Aachen)
- Seminar Current Milestones in Machine Learning and Computer Vision (RWTH Aachen)
- Physics Basic Lab Course (JLU Gießen)
Lecturer:
- Statistics for Geosciences (2021–2023, JLU Gießen)
Publications
Systematic Evaluation of Different Projection Methods for Monocular 3D Human Pose Estimation on Heavily Distorted Fisheye Images
Authors: Stephanie Käs, Sven Peter, Henrik Thillmann, Anton Burenko, Timm Linder, David Adrian, and Dennis Mack, Bastian Leibe
In this work, we tackle the challenge of 3D human pose estimation in fisheye images, which is crucial for applications in robotics, human-robot interaction, and automotive perception. Fisheye cameras offer a wider field of view, but their distortions make pose estimation difficult. We systematically analyze how different camera models impact prediction accuracy and introduce a strategy to improve pose estimation across diverse viewing conditions.
A key contribution of our work is FISHnCHIPS, a novel dataset featuring 3D human skeleton annotations in fisheye images, including extreme close-ups, ground-mounted cameras, and wide-FOV human poses. To support future research, we will be publicly releasing this dataset.
More details coming soon — stay tuned for the final publication! Looking forward to sharing our findings at ICRA 2025!
