Multi-modal human motion capture (mocap)
Supervision by: Dr. Stefanie Demirci
and Dr. Diana Mateus
In this project, we would like to investigate bridging the gap between human mocap in a variety of modalities. Specifically, as shown in the image below, given a patient lying on the bed, his actions and poses are simultaneously observed/recorded by various sensors e.g., RGBD sensors (Kinect), 3D motion capture system (ART), inertial sensors, and pressure sensors. Different modalities hold different characteristics. It would be beneficial to study how one helps the others.
Students will learn how to handle different types of acquisition equipment. The main activity is to perform experiments with different people, collect and verify the data. The experiments are hold in the Human Simulation Center in Klinikum LMU (Sendlinger Tor).
- We are looking for enthusiastic student with solid skills in C/C++ and Python programming.
- Experience in Computer Vision, Image Processing and/or Machine Learning is a plus.
If you are interested, please send your CV to firstname.lastname@example.org