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