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Seminar 3-D Vision Hackathon (SemHack)- Lecturer
- Dipl.-Ing. Peter Fürsattel
- Details
- Seminar
4 cred.h, benoteter certificate, compulsory attendance, ECTS studies, ECTS credits: 5
nur Fachstudium, Sprache Englisch
Time and place: n.V.; comments on time and place: Blockveranstaltung in der Woche vor Beginn des Wintersemesters
- Fields of study
- WPF INF-MA ab 1
WPF CE-MA-SEM ab 1
WPF IuK-MA ab 1
WPF MT-MA ab 1
- Prerequisites / Organisational information
- Strong experience with C/C++/C#.
Some experience with working on sensor data, ideally images Having visited at least one relevant lecture, project or seminar is recommended (e.g. Computer Vision lecture/project/seminar, DMIP, IMIP)
Individual registration via e-mail incl. motivation statement and report on programming skills is required to participate. Additional information will be available on the website linked below. - Contents
- The goal of this block seminar is to build an entire application using advanced computer vision technologies. The seminar consists of three parts and is structured like a hackathon.
1. Get inspired (day 1):
Experts from academia and / or industry will present different technologies like
mixed reality devices (e.g. Microsoft HoloLens) 3D cameras (e.g. Kinect, RealSense, Project Tango) and other computer vision related technology.
2. Build something fancy using the introduced technology (day 2-4).
3. Present your application (day 5).
During the seminar there will be mentoring and a limited number of devices (HoloLenses, cameras, etc.) provided.
- ECTS information:
- Credits: 5
- Additional information
- Keywords: computer vision; hackathon; holo-lens; mixed reality
Expected participants: 14, Maximale Teilnehmerzahl: 14
www: http://www5.cs.fau.de/lectures/ws-1718/seminar-3-d-vision-hackathon-semhack/
Registration is required for this lecture.
Die Registration via: persönlich beim Dozenten
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2017/2018:
- Seminar 3-D Vision Hackathon (SemHack)
- Department: Chair of Computer Science 5 (Pattern Recognition)
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