252-0579-00L  3D Vision

SemesterSpring Semester 2020
LecturersM. Pollefeys, V. Larsson
Periodicityyearly recurring course
Language of instructionEnglish


252-0579-00 G3D Vision3 hrs
Mon09:15-12:00CAB G 51 »
M. Pollefeys, V. Larsson
252-0579-00 A3D Vision1 hrsM. Pollefeys, V. Larsson

Catalogue data

AbstractThe course covers camera models and calibration, feature tracking and matching, camera motion estimation via simultaneous localization and mapping (SLAM) and visual odometry (VO), epipolar and mult-view geometry, structure-from-motion, (multi-view) stereo, augmented reality, and image-based (re-)localization.
ObjectiveAfter attending this course, students will:
1. understand the core concepts for recovering 3D shape of objects and scenes from images and video.
2. be able to implement basic systems for vision-based robotics and simple virtual/augmented reality applications.
3. have a good overview over the current state-of-the art in 3D vision.
4. be able to critically analyze and asses current research in this area.
ContentThe goal of this course is to teach the core techniques required for robotic and augmented reality applications: How to determine the motion of a camera and how to estimate the absolute position and orientation of a camera in the real world. This course will introduce the basic concepts of 3D Vision in the form of short lectures, followed by student presentations discussing the current state-of-the-art. The main focus of this course are student projects on 3D Vision topics, with an emphasis on robotic vision and virtual and augmented reality applications.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits5 credits
ExaminersM. Pollefeys, V. Larsson
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationNo final exam, but evaluation during semester (project).
Grading scheme:
1. 25%: Paper presentation (incl. discussion moderation)
2. 75%: Final project which includes a report and presentation/demo

Learning materials

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No information on groups available.


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