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/).
The course assistant is Antti Parviainen.
Course personnel has emails of the form firstname.lastname @ aalto.fi (i.e. juho.kannala, antti.parviainen).
Lectures are on Mondays from 10:15 to 12:00 in room T1 (CS building). The first lecture is on Monday September 9.
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 first exercise and deadline of weekly homework is on Friday September 13.
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 14:15 to 16:00 where teachers are available to give instructions for solving the homework. The first Thursday session is in Maari B classroom, and the following sessions in the first teaching period in C106 in CS building, and in the second teaching period in Y342a in Otakaari 1.
All the sessions and their locations can be found from the course calendar in MyCourses. Participation in the teaching sessions is not obligatory and not rewarded, but returning the homeworks is necessary and rewarded with bonus points.
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
You should check the exact time and location of the exams from Oodi. The main exam for the autumn edition of the course is in December. There will be additional exams in the spring term.
Programming skills and basic knowledge of data structures and mathematics (linear algebra, probability) will be necessary.