The working group explores technologies for capturing diverse human data across sensor types, employing machine learning methods. Emphasizing wearables for robust parameter measurement, contactless measurement using cameras, and motion estimation, they develop statistical methods and visualization tools for data analysis. The group prioritizes networking technologies that ensure data protection and security in the transmission of sensitive health data.
What are we offering?
Based in the Department of Epileptology, our research group explores advanced technologies to capture various human data. Specializing in motion capture, wearables and hardware development, including video EEG monitoring, we use machine learning for insightful analysis. With a focus on wearables for precise measurements and non-contact methods such as cameras, we use statistical methods and visualization tools to make sense of complex data. Ensuring data security, especially when transmitting sensitive health information, is of paramount importance to us. If your project touches on these areas, we are open to collaborations and willing to share our expertise and make a meaningful contribution to your research.
What are we interested in for collaboration?
We are seeking collaborations in applications that can leverage our expertise, specifically in the areas of motion capture, motion segmentation and classification, wearables, hardware development, and secure data transmission. If your project involves these aspects, we would be interested in exploring potential partnerships to contribute our knowledge and capabilities.
Discover our Lab page here.
5 selected publications
- Efficient Unsupervised Temporal Segmentation of Motion Data; Björn Krüger, Anna Vögele, Tobias Willig, Angela Yao, Reinhard Klein und Andreas Weber; In: IEEE Transactions on Multimedia (Apr. 2017), 19:4(797-812).
- A Dual-Source Approach for 3D Pose Estimation from a Single Image; Hashim Yasin, Umar Iqbal, Björn Krüger, Andreas Weber und Juergen Gall; In proceedings of IEEE Conference on Computer Vision and Pattern Recognition 2016 (CVPR).
- One Small Step for a Man: Estimation of Gender, Age, and Height from Recordings of One Step by a Single Inertial Sensor; Qaiser Riaz, Anna Vögele, Björn Krüger und Andreas Weber In: Sensors (Dez. 2015), 15:12(31999-32019).
- MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation; Jürgen Bernard, Nils Wilhelm, Björn Krüger, Thorsten May, Tobias Schreck und Jörn Kohlhammer; In: IEEE Transactions on Visualization and Computer Graphics (Dez. 2013).
- Motion Reconstruction Using Sparse Accelerometer Data; Jochen Tautges, Arno Zinke, Björn Krüger, Jan Baumann, Andreas Weber, Thomas Helten, Meinard Müller, Hans-Peter Seidel und Bernd Eberhardt; In: ACM Trans. Graph. (Mai 2011), 30:3(18:1-18:12).