Medizinische Bewegungsanalyse bei Kleinkindern

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Infant motion analysis enables early detection of neurodevelopmental disorders like cerebral palsy (CP). The quality of spontaneous movements, in particular of the general movements (GMs), at the corrected age of 2-4 months accurately reflects the state of the infant's nervous system. The general movement assessment (GMA) method achieves the highest reliability for the detection of CP at an early age. In order to remove the human variability and the effort of regular training of GMA experts, we aim at automating medical infant motion analysis.


The Skinned Multi-Infant Linear model (SMIL)




Learning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis
Hesse, N., Pujades, S., Romero, J., Black, M. J., Bodensteiner, C., Arens, M., Hofmann, U. G., Tacke, U., Hadders-Algra, M., Weinberger, R., Müller-Felber, W., Schroeder, A. S.
In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), September 2018
pdf supplementary results video extended paper extended video DOI bib

The SMIL model is available for research purposes.
To download the SMIL model, please click the following button:


By downloading and/or using the model, you agree to the license terms, which can be found here.


The Moving INfants In RGB-D (MINI-RGBD) data set




Computer Vision for Medical Infant Motion Analysis: State of the Art and RGB-D Data Set
Hesse, N., Bodensteiner, C., Arens, M., Hofmann, U. G., Weinberger, R., Schroeder, A. S.
In European Conference on Computer Vision Workshops (ECCVW), September 2018
pdf bib video

By downloading and/or using the data set, you agree to the license terms, which can be found here.
Note: The infants shown in the images above / the video / the paper / the data set were created using the SMIL model with generated textures and shapes and therefore do not depict any existing infants.

To download the data set, please click the following button:


After unzipping the .zip file, you'll find a README.txt that explains the folder and data structures.


Contact


Nikolas Hesse
Christoph Bodensteiner

Publications