Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course FMA271F valid from Autumn 2013

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  • English
  • Every spring semester
  • The aim of the course is to give necessary knowledge for further research within computer vision and in order to use computer vision methods within other research areas, e.g. robotics, vision systems, non-invasive measurements and augmented reality.
  • Projective geometry. Geometric transformations. Modelling cameras. Stereo vision. Photogrammetry. Recognition. 3D-modelling. Geometry of surfaces and their silhouettes. Visualisation.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • be able to clearly explain and use basic concepts in computer vision, in particular regarding projective geometry, camera modelling, stereo vision, recognition and structure and motion problems.

    be able to describe and give an informal explanation of the mathematical theory behind some central algorithms in computer vision (the least squares method and Newton based optimization).
Competences and Skills
  • For a passing grade the doctoral student must
  • in an engineering manner be able to use computer packages to independently solve problems in computer vision.

    be able to show good ability to independently identify problems which can be solved with methods from computer vision, and be able to choose an appropriate method.

    be able to independently apply basic methods in computer vision to problems which are relevant in industrial applications or research.

    with proper terminology, in a well-structured way and with clear logic, be able to explain the solution to a problem in computer vision.
Judgement and Approach
  • For a passing grade the doctoral student must
Types of Instruction
  • Lectures
  • Laboratory exercises
  • Exercises
Examination Formats
  • Written exam
  • Oral exam
  • Written assignments
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
Selection Criteria
  • Szeliski, R.: Computer Vision: Algorithms and Applications. Springer, 2010. ISBN 9781848829343.
  • It is possible to pass the course using handouts.
Further Information
Course code
  • FMA271F
Administrative Information
  •  -01-31
  • FN1/Anders Gustafsson

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