|Abstract||For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the key computer vision algorithms used in mobile robotics, such as feature extraction, multiple view geometry, dense reconstruction, tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithms behind Google Tango, Ms Hololens, and the Mars rovers).|
|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||Each lecture will be followed by a lab session where you will learn to implement the building block of a visual odometry algorithm in Matlab. By the end of the course, you will integrate all these building blocks into a working visual odometry algorithm.|
|Lecture notes||Lecture slides will be made available on the course official website: http://rpg.ifi.uzh.ch/teaching.html|
|Literature|| Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010. |
 Robotics Vision and Control: Fundamental Algorithms, by Peter Corke 2011.
 An Invitation to 3D Vision, by Y. Ma, S. Soatto, J. Kosecka, S.S. Sastry.
 Multiple view Geometry, by R. Hartley and A. Zisserman.
 Introduction to autonomous mobile robots 2nd Edition, by R. Siegwart, I.R. Nourbakhsh, and D. Scaramuzza, February, 2011
|Prerequisites / Notice||Fundamentals of algebra, geomertry, matrix calculus, and Matlab programming.|