263-5902-00L  Computer Vision

SemesterAutumn Semester 2018
LecturersM. Pollefeys, V. Ferrari, L. Van Gool
Periodicityyearly recurring course
Language of instructionEnglish

Catalogue data

AbstractThe goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.
ObjectiveThe objectives of this course are:
1. To introduce the fundamental problems of computer vision.
2. To introduce the main concepts and techniques used to solve those.
3. To enable participants to implement solutions for reasonably complex problems.
4. To enable participants to make sense of the computer vision literature.
ContentCamera models and calibration, invariant features, Multiple-view geometry, Model fitting, Stereo Matching, Segmentation, 2D Shape matching, Shape from Silhouettes, Optical flow, Structure from motion, Tracking, Object recognition, Object category recognition
Prerequisites / NoticeIt is recommended that students have taken the Visual Computing lecture or a similar course introducing basic image processing concepts before taking this course.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits6 credits
ExaminersM. Pollefeys, V. Ferrari, L. Van Gool
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationThe grade will be determined by a) a written final exam and b) homework exercises performed during the semester (compulsory continuous performance assessment). Specifically, the final grade will be 3/4 final exam and 1/4 exercises.
Written aidsNone
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

Main linkInformation
Only public learning materials are listed.


263-5902-00 VComputer Vision3 hrs
Wed13-16CHN C 14 »
M. Pollefeys, V. Ferrari, L. Van Gool
263-5902-00 UComputer Vision1 hrs
Thu15-16CHN C 14 »
M. Pollefeys, V. Ferrari, L. Van Gool
263-5902-00 AComputer Vision1 hrsM. Pollefeys, V. Ferrari, L. Van Gool


No information on groups available.


There are no additional restrictions for the registration.

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