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  Seminar – Road Scene Understanding for the Visually Impaired (SemRSUVI)

Dozentinnen/Dozenten
Hakan Calim, Prof. Dr.-Ing. habil. Andreas Maier

Angaben
Seminar
Online
2 SWS, ECTS-Studium, ECTS-Credits: 5, Sprache Deutsch und Englisch
Zeit: Fr 8:15 - 9:30, 09.150

Inhalt
Understanding road scenes and creating maps from urban environments is a challenging task in Computer Vision. It is used in self-driving cars, robotics and assistive navigation systems for blind or visually impaired pedestrians. The topic of this seminar will be to build a software tools that will enable the creation of a navigation assistant for the blind and visually impaired. In particular the following issues will be addressed:
1. Define the hardware resources (e.g. computational resources, camera/cell phone, TOF/Lidar/focal length, sensors, ...)
2. Set up a web-based collaborative labeling environment using crowd-based labeling tools (e.g. EXACT (https://github.com/ChristianMarzahl/Exact))
3. define guidelines for crowdsourced labeling
4. Define use cases (face recognition, license plates) for managing and anonymizing the data.
The aim of this project seminar is to build tools that will enable preparation of data, e.g. image segmentation of roads, sidewalks and obstacles, etc. In a second step, the data should be ready for the creation of maps and respective annotations from the scenes so it can be used building for an assistive navigation system for blind or visually impaired pedestrians.

Empfohlene Literatur

ECTS-Informationen:
Credits: 5

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 30
www: https://www.studon.fau.de/crs4070112.html

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2022/2023:
Seminar – Road Scene Understanding for the Visually Impaired (SemRSUVI)

Institution: Lehrstuhl für Informatik 5 (Mustererkennung)
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