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  Seminar Computer Stereo Vision (SemCSV)

Dozentinnen/Dozenten
Dipl.-Ing. Peter Fürsattel, André Aichert, M. Sc.

Angaben
Seminar
4 SWS, ECTS-Studium, ECTS-Credits: 5, Sprache Englisch
Zeit und Ort: Einzeltermine am 14.10.2015, 21.10.2015 14:00 - 16:00, 01.134; 16.12.2015 9:00 - 12:00, 00.156-113; 16.12.2015 13:00 - 17:00, 01.134; 13.1.2016, 20.1.2016 13:00 - 17:00, 01.134; Bemerkung zu Zeit und Ort: Vergabe der Themen und Termine in der ersten Semesterwoche

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 Stereo Vision.

The goal of this seminar is to provide an overview of the algorithms involved in extracting geometric information, notably depth, from two digital images.

Individual topics cover one specific aspect of such a system, ranging from the geometry and calibration of a single camera, feature detection and description, feature matching and the estimation of epipolar geometry, to rectification and disparity estimation, as well as view interpolation.

In the beginning of the term, there will be two introductory classes about projective geometry and the pinhole camera model. The final presentations will be blocked in two or three days some time at the end of the semester.

The grade is composed to 50% of a final presentation and 50% of a 6 pages seminar paper (IEEE style). Optionally, participants may opt to provide a demonstration of a working prototype after their presentation and write a shorter 3 pages seminar paper.

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-1516/seminar-computer-stereo-vision-semcsv/

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2015/2016:
Seminar Computer Stereo Vision (SemCSV)

Institution: Chair of Computer Science 5 (Pattern Recognition)
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