DaARTMocapBed

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Multi-modal human motion capture (mocap)

Supervision by: Dr. Stefanie Demirci and Dr. Diana Mateus
Contact: motioncap@mailnavab.informatik.tu-muenchen.de

Project Description

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).

regularizing predictions by conditional random field

Requirements

  • 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.

Contact

If you are interested, please send your CV to motioncap@mailnavab.informatik.tu-muenchen.de.




Students.ProjectForm
Title: Multimodal Human Mocap
Abstract:  
Student:  
Director: Dr. Nassir Navab
Supervisor: Dr. Stefanie Demirci, Dr. Diana Mateus
Type: DA/MA/BA
Area: Machine Learning, Computer Vision
Status: finished
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.6 - 02 Jan 2019 - 11:43 - TobiasLasser