LFU:online

Computer Vision is a very broad field and as old as Computer Science itself. Why vision? Many of the most successful life forms have evolved incorporating visual information as one of the main sources of knowledge extraction to interact with the environment. In humans more than half of neurons in the brain dedicated to the senses are involved in analyzing information that comes through the eyes. Many computer systems consider visual information as their input, needing to analyze and extract knowledge from static images or a succession of them. Iris and fingerprint recognition for identity, automatic camera surveillance, face and object recognition, motion tracking, robotics and humanoids, or developing devices for the visually impaired are some of the applications of Computer Vision. In this course we study all the areas that comprise Computer Vision and look deeper into some of the most relevant and successful methods that have been presented until the present time.

Image formation, camera geometry, object recognition, stereopsis, motion, structure from motion, object detection, convolutional neural networks, machine learning in computer vision

Lecture, assessment is based on a single examination at the end of the course.

Written exam

• Required: Visual Computing
• Required but can be done parallel to this course: Machine Learning

Allocation of places in courses with a limited number of participants (PS, SE, VU, PJ)

In courses with a limited number of participants, course places are allocated as follows:

1. Students for whom the study duration would be extended due to the postponement are to be given priority.

2. If the criteria in no. 1 do not suffice, first, students for whom this course is part of a compulsory module are to be given priority, and second, students for whom this course is part of an elective module.

3. If the criteria in no. 1 and 2 do not suffice, the available places are drawn by random.

Curriculum BA Computer Science 2019