Development of machine learning techniques for movement analysis
[Closed]
Work description
Our group has a long standing experience in movement analysis for biomedical applications. One of our research lines is focusing on movement based epileptic seizure classification. Our earlier approaches proved the feasibility and advantages of an action recognition approach. In order to further advance the system it is required to utilize 3D MoCap for in-bed scenarios, where one of the main source of occlusions is the blanket, therefore this work aims to research synthetic blanket occlusion augmentation.
Academic Qualifications
Master's degree in Electrical and Computer Engineering, Informatics, Biomedical Engineering, or other similar areas.
Minimum profile required
Previous knowledge in computer vision tasks, software development (Python, C++/C# ...) and experience in machine learning frameworks (PyThorch, Tensorflow, ...). Proven experience in integrating 3D computer graphics engines (Blender, ...) into machine learning pipelines.
Preference factors
Good understanding and experience in computer vision, particularly in 3D motion capture and action recognition.
Application Period
Since 28 Dec 2022 to 10 Jan 2023
[Closed]
Centre
Biomedical Engineering Research