This course provides an introduction to computer vision including fundamentals of image formation & filtering, feature detection & matching, structure-from-motion & image-based 3D modelling, motion estimation & tracking, and object detection & recognition. The course gives an overview of algorithms, models and methods, which are used in automatic analysis of visual data.
The course will be lectured by Assistant Professor Juho Kannala (https://users.aalto.fi/~kannalj1/).
Course assistants are Zakaria Laskar and Santiago Cortes Reina.
Course personnel has emails of the form firstname.lastname @ aalto.fi (i.e. juho.kannala, santiago.cortesreina, zakaria.laskar).
Lectures are on Mondays from 10:15 to 12:00 in room T1 (CS building). The first lecture is on Monday September 11.
Exercises are on Fridays from 12:15 to 14:00 in room TU1 (TUAS building) during the first teaching period and in room T1 (CS building) during the second teaching period.
The deadline of weekly homework exercises is at noon on Fridays and the solutions are presented in Friday's exercise sessions. In addition, there is a guidance session every Thursday from 16:15 to 18:00 in U257 at the Undergraduate Center (Otakaari 1) where assistants are available to give instructions for solving the homework.
Registration and requirements
Aalto students should register via Oodi.
The requirements for passing the course are as follows:
- Get more than 0 points from at least 8 weekly exercise rounds (see "Assignments"-page)
- Pass the exam
Programming skills and basic knowledge of data structures and mathematics (linear algebra, probability) will be necessary. Students are encouraged to use Matlab in the programming exercises and therefore previous experience with Matlab is beneficial.