227-0447-00L  Image Analysis and Computer Vision

Semester Autumn Semester 2017
Lecturers L. Van Gool, O. Göksel, E. Konukoglu
Periodicity yearly course
Language of instruction English



Catalogue data

Abstract Light and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation and deformable shape matching. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition.
Objective Overview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.
Content The first part of the course starts off from an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First it is investigated how the parameters of the electromagnetic waves are related to our perception. Also the interaction of light with matter is considered. The most important hardware components of technical vision systems, such as cameras, optical devices and illumination sources are discussed. The course then turns to the steps that are necessary to arrive at the discrete images that serve as input to algorithms. The next part describes necessary preprocessing steps of image analysis, that enhance image quality and/or detect specific features. Linear and non-linear filters are introduced for that purpose. The course will continue by analyzing procedures allowing to extract additional types of basic information from multiple images, with motion and depth as two important examples. The estimation of image velocities (optical flow) will get due attention and methods for object tracking will be presented. Several techniques are discussed to extract three-dimensional information about objects and scenes. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed.
Lecture notes Course material Script, computer demonstrations, exercises and problem solutions
Prerequisites / Notice Prerequisites:
Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Linux and C.
The course language is English.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits 6 credits
Examiners O. Göksel, E. Konukoglu, L. Van Gool
Type session examination
Language of examination English
Course attendance confirmation required No
Repetition The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examination oral 15 minutes
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main link Information
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Courses

Number Title Hours Lecturers
227-0447-00 V Image Analysis and Computer Vision 3 hrs
Thu 13-16 ETF C 1 »
L. Van Gool, O. Göksel, E. Konukoglu
227-0447-00 U Image Analysis and Computer Vision 1 hrs
Thu 16-17 ETF C 1 »
L. Van Gool, O. Göksel, E. Konukoglu

Restrictions

There are no additional restrictions for the registration.

Offered in

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Computational Science and Engineering Master Electives W Information
Robotics, Systems and Control Master Core Courses W Information