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Seit WiSe 2022/23


Introduction to Camera Geometry


Gallego, Guillermo




Fakultät IV

Institut für Technische Informatik und Mikroelektronik

34342000 FG Robotic Interactive Perception

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MAR 5-5

Mestre, Bianca


Learning Outcomes

How does a photographic camera capture the world? The course is an introduction to the geometry of the image formation process and how visual data is represented and manipulated in a computer. We will learn projective geometry, which helps us model the perspective projection, and digital image processing. We will be answering the following questions: - How can we model the perspective operation that happens when we take a picture? (Projective Geometry, Image formation process). - How are pictures (visual data) represented and processed in a computer? (Digital image processing). - How can we find out the internal geometric parameters of a camera? (Camera Calibration). - What applications does camera technology have in robotics? (Stereopsis, Visual odometry, AR/VR, etc.)


In the lectures we will discuss and study some of computer vision related topics: - Image formation process - Projective Geometry - Digital image processing - Camera Calibration - Applications: Stereopsis, Visual odometry, AR/VR

Module Components


All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Introduction to Camera GeometrySeminarSoSeEnglish2

Workload and Credit Points

Introduction to Camera Geometry (Seminar):

Workload descriptionMultiplierHoursTotal
Pre/post processing15.04.0h60.0h
90.0h(~3 LP)
The Workload of the module sums up to 90.0 Hours. Therefore the module contains 3 Credits.

Description of Teaching and Learning Methods

Teaching and Learning methods: in-presence lectures, with projector and explanations in whiteboard. Students must prepare reading material in advance to participate actively during the lectures. Learning by reading, studying and practicing with exercises. Exercises and projects carried out in groups (of 2-3 students).

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Knowledge of analytical geometry, Linear Algebra, discrete signal processing, and some programming Language (Matlab, Python, etc.) to practice with exercises. Curiosity and motivation to learn new topics is a prerequisite.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion



Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt



Test elements

(Deliverable assessment) Project, including presentation50practicalProgramming or paper study
(Deliverable assessment) Assessment of concepts (written)50flexible30 - 60 min

Grading scale

Notenschlüssel »Notenschlüssel 1: Fak IV (1)«


Test description (Module completion)

The exam consist of multiple choice questions and also questions to develop more openly, without multiple choice.

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

The students can sign in without a homework. They just need to sign in via the Metaseite der Seminare in ISIS.

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable


Electronical lecture notes

Availability:  unavailable



Recommended literature
R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision, 2nd Ed, Cambirdge UP 2003. https://doi.org/10.1017/CBO9780511811685
R. Szeliski, Computer Vision: Algorithms and Applications. https://szeliski.org/Book/

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Informatik (B. Sc.)14WiSe 2022/23SoSe 2024
Medientechnik (B. Sc.)14WiSe 2022/23SoSe 2024
Technische Informatik (B. Sc.)14WiSe 2022/23SoSe 2024
Wirtschaftsinformatik (B. Sc.)25WiSe 2022/23SoSe 2024


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