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Medizintechnik (Master of Science) >>
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Seminar Computer Vision (SemCV)- Dozent/in
- Dipl.-Ing. Peter Fürsattel
- Angaben
- Seminar
4 SWS, ECTS-Studium, ECTS-Credits: 5, Sprache Englisch
Zeit und Ort: Einzeltermine am 30.1.2017 12:00 - 14:00, 01.134; 2.2.2017 8:00 - 10:00, 01.134; 7.2.2017 10:00 - 12:00, 01.134; Bemerkung zu Zeit und Ort: Vergabe der Themen und Termine zu Beginn des Semesters
Vorbesprechung: 24.10.2016, 12:00 - 14:00 Uhr, Raum 01.134
- Studienfächer / Studienrichtungen
- WPF INF-MA ab 1
WPF CE-MA-SEM ab 1
WPF IuK-MA ab 1
- Inhalt
- This seminar discusses individual algorithms and applications of computer vision. The goal of this seminar is to introduce students to selected aspects of computer vision. In this term, we will cover algorithms for 2.5D scene analysis, forgery detection for video sequences and potentially other current research topics.
In the beginning of the term, there will be an introductory meeting to discuss the organization of the project and for presenting the individual topics.
During the term you will have time to prepare a presentation and your implementation/paper. The final presentations will be held at the end of the term. The grade consists of two parts: the final presentation of the topic and a seminar paper or an implementation. Each participant can choose between writing a 6 pages seminar paper (IEEE style), or creating an implementation/demonstrator, including a short documentation. Please visit the website below for additional information.
- Empfohlene Literatur
- Hartley R. and Zisserman A.: "Multiple View Geometry in Computer Vision", Cambridge University Press, 2004
- ECTS-Informationen:
- Credits: 5
- Zusätzliche Informationen
- Schlagwörter: computer vision, pinhole camera model, stereo vision
Erwartete Teilnehmerzahl: 10
www: http://www5.cs.fau.de/lectures/ws-1617/seminar-computer-vision-semcv/
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2016/2017:
- Seminar Computer Vision (SemCV)
- Seminar Medizintechnik und Medizinethik (Medtech Ethik)
- Institution: Lehrstuhl für Informatik 5 (Mustererkennung)
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