3D Computer Vision

Module IN2057

This Module is offered by TUM Department of Informatics.

This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.

Basic Information

IN2057 is a semester module in English language at Bachelor’s level und Master’s level which is offered in summer semester.

This Module is included in the following catalogues within the study programs in physics.

  • Catalogue of non-physics elective courses
Total workloadContact hoursCredits (ECTS)
150 h 60 h 5 CP

Content, Learning Outcome and Preconditions


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"

Learning Outcome

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

Courses, Learning and Teaching Methods and Literature

Courses and Schedule

VU 4 3D Computer Vision (IN2057) Montag, 14:00–16:00
Dienstag, 15:00–16:30

Learning and Teaching Methods

lecture, exercise course, problems for individual study




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

Module Exam

Description of exams and course work

In the written exam 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.

Exam Repetition

There is a possibility to take the exam at the end of the semester.

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