Moses - Introduction to Camera Geometry

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Module / Version:
#41060 / #1

Validity:
Seit WiSe 2022/23

Default display language:
English

Module title:
Introduction to Camera Geometry

Credits:
3

Responsible person:
Gallego, Guillermo

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Technische Informatik und Mikroelektronik

Area of expertise:
34342000 FG Robotic Interactive Perception

Prüfungsausschuss:
No information

Kontakt

Office:
MAR 5-5

Contact person:
Mestre, Bianca

E-mail address:
guillermo.gallego@tu-berlin.de

Website:

https://isis.tu-berlin.de/course/view.php?id=29903

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.)

Content

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

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Introduction to Camera Geometry	SEM		SoSe	English	2

Workload and Credit Points

Introduction to Camera Geometry (SEM):

Workload description	Multiplier	Hours	Total
Attendance	15.0	2.0h	30.0h
Pre/post processing	15.0	4.0h	60.0h
			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

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

English

Test elements

Name	Points	Categorie	Duration/Extent
(Deliverable assessment) Project, including presentation	50	practical	Programming or paper study
(Deliverable assessment) Assessment of concepts (written)	50	flexible	30 - 60 min

Grading scale

Notenschlüssel »Notenschlüssel 1: Fak IV (1)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	86.0pt	82.0pt	78.0pt	74.0pt	70.0pt	66.0pt	62.0pt	58.0pt	54.0pt	50.0pt

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:
Sommersemester.

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 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

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

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

Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
Informatik (B. Sc.)	1	4	WiSe 2022/23	SoSe 2024
Medientechnik (B. Sc.)	1	4	WiSe 2022/23	SoSe 2024
Technische Informatik (B. Sc.)	1	4	WiSe 2022/23	SoSe 2024
Wirtschaftsinformatik (B. Sc.)	2	5	WiSe 2022/23	SoSe 2024

Miscellaneous

No information

Introduction to Camera Geometry