151-0632-00L Vision Algorithms for Mobile Robotics

Semester	Autumn Semester 2016
Lecturers	D. Scaramuzza
Periodicity	yearly recurring course
Language of instruction	English
Comment	Number of participants limited to 50

Abstract	For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango).
Objective	Learn the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango).
Content	For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the fundamental computer vision algorithms used in mobile robotics, in particular: feature extraction, multiple view geometry, dense reconstruction, object tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithm behind Google Tango).
Lecture notes	Lecture slides will be available after each lecture on the course official website: http://rpg.ifi.uzh.ch/teaching.html
Literature	[1] Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010. [2] Robotics Vision and Control: Fundamental Algorithms, by Peter Corke 2011.
Prerequisites / Notice	Basics of algebra and geomertry, matrix calculus.

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits	4 credits
Examiners	D. Scaramuzza
Type	session examination
Language of examination	English
Repetition	The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examination	oral 30 minutes
Additional information on mode of examination	70% of the final grade is based on the oral exam, 30% on an individual mini project. A list of possible mini projects will be out by the 3rd week of the course. Students can also propose their own mini project.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.


Main link	Slides of the course
Literature	Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010.
	Robotics Vision and Control: Fundamental Algorithms, by Peter Corke 2011.
Only public learning materials are listed.