Lecture: Augmented Reality

15th September 2017
Lecture: Augmented Reality

Lecturer: Prof. Aljosa Smolic. This course will cover fundamentals and state-of-the-art in augmented reality, as well as related areas of 3D computer vision and graphics.

Module Code CS7GV4
Module Name Augmented Reality
Module Short Title
ECTS 5
Semester Taught HT
Contact Hours 2 lecture hours and 1 lab hour per week
Module Personnel Professor Aljosa Smolic
Learning Outcomes On successful completion of this module, students will be able to:

  • Review and asses the state-of-the-art in augmented reality technologies
  • Develop an augmented reality solution (project) including implementation, testing, evaluation, demonstration, and documentation
  • Come up with own ideas for an augmented reality project
Learning Aims This course will cover fundamentals and state-of-the-art in augmented reality, as well as related areas of 3D computer vision and graphics. Theoretical background as well as practical solutions and applications will be presented in the lectures. Students will get direct exposure to latest research results of Prof. Smolic’s research team V-SENSE. In their own work, students will be asked to design an own project (individual or groups) from idea, via implementation, testing, evaluation, demonstration, to documentation. In this way they will experience the full lifecycle of a practical project, as they will face it once they leave the university in either industry or research. A default project will be suggested as fallback, still covering the full lifecycle except the idea.
Module Content Specific topics addressed in this module will include:

  • Camera model and calibration
  • Fundamentals of 3D computer vision and multiview geometry (fundamental and essential matrix)
  • Structure-from-motion
  • SLAM
  • Shape-from-silhouette, visual hulls
  • Depth and disparity estimation
  • Homographies, warping, panoramas, 360/VR video
  • Free viewpoint video
  • Hardware devices and tools
  • Software packages
Recommended Reading List Fundamentals of computer vision in any form, e.g.

Computer Vision: Algorithms and Applications, Richard Szeliski, September 3, 2010 draft, 2010 Springer

http://szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf

Multiple View Geometry in Computer Vision

Second Edition

Richard Hartley and Andrew Zisserman,

Cambridge University Press, March 2004.

http://www.robots.ox.ac.uk/~vgg/hzbook/
Module Prerequisites Some background in fundamentals of computer vision and graphics will be helpful but not necessarily required.
Assessment Details Annual Assessment=100% coursework (project):

Students will be asked to design an own project (individual or groups) from idea, via implementation, testing, evaluation, demonstration, to documentation. A default project will be suggested as fallback.

Supplemental Assessment=100% coursework
Module Website
Academic Year of Data 2017/18
CategoryLectures