Computer Vision (ECOVI)

M.Sc. studies - EMARO and "Robotics" (MEiL Faculty)

Winter 2017/2018


Contents:


Meeting times and locations

Lecture:
Friday, 12:15-14:00 (i.e. 12:15 p.m.- 2:00 p.m.), room 528, E&IT Faculty

Tutorial:
Wednesday (every second week), 16:15-18:00, lab. P114, E&IT Faculty

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Teaching staff and contact info

prof. Włodzimierz Kasprzak
Office: room 565, E&IT Faculty, Institute of Control and Computation Eng.
Office hours: Monday OR Friday, 14.00-15.00
Phone: +22 234 7866
W.Kasprzak at elka.pw.edu.pl

Maciej Stefańczyk, M.Sc.
Office: room 564, E&IT Faculty, Institute of Control and Computation Eng.
Office hours:
Phone: +22 234 xxxx
M.Stefanczyk at elka.pw.edu.pl

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Short course description

Course objectives This course provides an introduction to computer vision from the perspective of robotics. Three parts are distinguished: 2-D image representation and processing, 3-D scene reconstruction, image sequence analysis. Topics include: projective geometry and camera calibration, 2-D image analysis - filtering, segmentation, 2-D object classification, stereo-vision, structure-from-motion, RGB-D image processing, image motion estimation, 3-D object tracking, vision-based navigation, visual SLAM.

Prerequisities
Students are expected to have the following background:

Course materials
Lecture notes will be posted periodically on the course web site. Selected chapters from the books below are recommended as optional reading.

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Marks and Grading

Assessment will be marked out of a hundred. The marks equate to ECTS grades as given below:
ECTS Grade A B C D E F/FX
mark 100- 91 90-81 80-71 70-61 60-51 50 or less
Students are collecting assessment points. They come from a continuous assessment in the semester time: The assessment method of this course consists of: In addition to satisfying the above assessment requirements, each student must satisfy the attendance requirements. There is an obligatory attendance of exercises and laboratory and an optional attendance of the lecture. The Pass mark for this course will be set at 51 pts. Credits will be awarded to candidates who pass this course.

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Lecture

Lecture schedule (tentative):