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CDH

Seminar/Thesis: Automated 3D body landmarks detection

Background

Nowadays the new digital modelling techniques can speed up the personalisation of wearables as well as the rapid prototyping. However, the personalisation might require very precise human body measurements which can be tedious if done manually. The project aims at implementing a convenient algorithm for the automatic detection of upper body landmarks necessary for the development of smart clothes.

Aim

Apply algorithms to extract automatically 3D upper body landmarks from digital human models.

Learning objectives

  • Analyse antrhopometric data from 3D human body models
  • Apply algorithms to extract upper body landmarks automatically

Data

Project type Seminar (optional: Master thesis)
ECTS 2.5, 5, 7.5, default: 5
Language English
Period Winter term 2020/21
Presence time Virtual seminar, working from remote
Useful knowledge Machine learning, Python, Image Processing
Work distribution 60% programming, 40% algorithms
Med. Eng. designation Advanced Context Recognition (ACR)
StudOn link Please join
First Meeting online-introduction-vorbesprechung-of-winter-term-2020-seminars, on 4th November 2020 at 16:15
Registration Via StudOn, obligatory after introduction

Literature

Up-to-date literature recommendations are provided during the lectures.

Examination

Final presentation and final report.

Contact

Annalisa Baronetto

  • Job title: Researcher
  • Address:
    Henkestraße 91, Haus 7, 1. OG
    91052 Erlangen
    Germany
  • Phone number: +49 9131 85 23608
  • Email: annalisa.baronetto@fau.de