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3D Computer Vision

Modul IN2057

Dieses Modul wird durch Fakultät für Informatik bereitgestellt.

Diese Modulbeschreibung enthält neben den eigentlichen Beschreibungen der Inhalte, Lernergebnisse, Lehr- und Lernmethoden und Prüfungsformen auch Verweise auf die aktuellen Lehrveranstaltungen und Termine für die Modulprüfung in den jeweiligen Abschnitten.


IN2057 ist ein Semestermodul in Englisch auf Bachelor-Niveau und Master-Niveau das im Sommersemester angeboten wird.

Das Modul ist Bestandteil der folgenden Kataloge in den Studienangeboten der Physik.

  • Allgemeiner Katalog der nichtphysikalischen Wahlfächer
GesamtaufwandPräsenzveranstaltungenUmfang (ECTS)
150 h 60 h 5 CP

Inhalte, Lernergebnisse und Voraussetzungen


Making a computer see was something that leading experts in the field of Artificial Intelligence thought to be at the level of difficulty of a summer student's project back in the sixties. Forty years later the task is still unsolved and seems formidable. A whole field, called Computer Vision, has emerged as a discipline in itself with strong connections to mathematics and computer science and looser connections to physics, the psychology of perception and the neuro sciences.

Over the past decade there has been a rapid development in the understanding and modelling of the geometry of multiple views in computer vision. The theory and practice have now reached a level of maturity where excellent results can be achieved for problems that were unsolved a decade ago, and often thought unsolvable. These tasks and algorithms include problems like: Given two/three/multiple images, and no further information, compute/estimate:
- matches between the images
- the 3D position of the points that generate these matches
- the cameras that generate the images

Adapted from Hartley & Zisserman's "Multiple View Geometry in Computer Vision"


After attending the module, the participants know and understand the basics of projective 2D and 3D geometry. They can handle the fundamental methods of computer vision: parameter estimation of 2D and 3D transformations/projections, error propagation, camera calibration and 3D reconstruction using two or more views.


MA0901 Linear Algebra for Informatics, MA0902 Analysis for Informatics

Lehrveranstaltungen, Lern- und Lehrmethoden und Literaturhinweise

Lehrveranstaltungen und Termine

VU 4 3D Computer Vision (IN2057) Mo, 14:00–16:00, 5620.01.101
Di, 15:00–16:30, 5620.01.101

Lern- und Lehrmethoden

Lecture, exercise course, problems for individual study




Hartley & Zisserman - "Multiple View Geometry in Computer Vision"


Beschreibung der Prüfungs- und Studienleistungen

In the written exam of 75 minutes the participants have to prove that, without using any further help, they are able to understand and describe problems of computer vision. The questions cover all topics of the lecture and should show that the participant is able to apply the concepts of projections, transformations and geometry estimation to provided problems and that the participant knows the established algorithms to accomplish these tasks. The exam can contain assignments where participants have to derive mathematical properties or need to provide graphical explanations.


Eine Wiederholungsmöglichkeit wird am Semesterende angeboten.

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