Thesis: Developing a Framework for Motion Data Synthesis

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From a classical marker-based motion capture system (MoCap) you obtain the coordinates of placed markers, which are used to establish a biomechanical model. However, information of the subject’s circumferences (silhouette) and surface effects is not provided, which is crucial in case of surface attached sensor synthesis. New digital modelling techniques can help to approximate subject’s silhouette based on the marker coordinates and allow a more realistic synthesis performance.


Extend the existing framework from real Motion Capture data to surface shape models while walking and running, developed at the chair. Use 3D modeling techniques (blender), automatic human body rigging and personalized shape models to synthesise different sensor signals in order to evaluate sensor placement effects.


Project type BA/MA Thesis
ECTS 10/30
Language English/ German
Period Summer term 2021
Presense time Virtual, working from remote, depending on the needs
Useful knowledge 3D modeling, programming, biomechanics
Work distribution 70% programming and algorithm development, 30% simulation
Med. Eng. designation Advanced Context Recognition (ACR)
StudOn link Please join
First meeting online-introduction-vorbesprechung-of-summer-term-2021-seminars, on 12th April 2021 at 16:15
Registration E-Mail to


Literature recommendations are provided during the meetings. The candidate is further encouraged to research relevant publications on this topic.


Final presentation and final report/thesis


Lena Uhlenberg

  • Job title: Researcher
  • Address:
    Henkestraße 91, Haus 7, 1. OG
    91052 Erlangen
  • Phone number: +49 9131 85-23605
  • Email:

Friedrich-Alexander-Universität Erlangen-Nürnberg