MeMoMan: Markerless Tracking of Human Motions
We are developing new computational models and a system for accurate measurement of human motion. Our primary goal is to develop markerless vision-based tracking algorithms for use with the industry-proven anthropometric human model RAMSIS (in collaboration with the TUM Ergonomics Department/Faculty of Mechanical Engineering). By providing RAMSIS with markerless tracking capabilities, we open up new fields of application in ergonomic studies and industrial design. On the other hand, we believe that a far-developed, flexible and accurate model such as RAMSIS is beneficial for human motion tracking given the ergonomic expertise that has affected its design.

Prof. Michael Beetz PhD
Head of Institute
Managing Directors:
Dr. habil. Hagen Langer
Sabine Veit
http://ai.uni-bremen.de
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