Computer Vision

Image formation and filtering, including:
-Camera and optics
-Light and color
-Image filtering
Image processing
Feature detection and matching
Image compression
Multiple views and stereo
Recognition
Segmentation
Color imaging
Introduction to spectral imaging
Introduction to machine learning
Applications, including for example the following;
-Face detection
-Face recognition
-OCR
-Industrial applications
-Medical imaging
-Image stitching

Knowledge:
-identify basic concepts, terminology, theories, models and methods in the field of computer vision
-describe basic methods of computer vision related to multi-scale representation, edge detection and detection of other primitives, stereo, motion and object recognition.
-assess which methods to use for solving a given problem, and analyse the accuracy of the methods

Skills:
-develop and apply computer vision techniques for solving practical problems
-choose appropriate image processing methods for image filtering, image restoration, image reconstruction, segmentation, classification and representation,

General competence:
-acquire good and practical skills in computer vision.

-Lectures
-Exercises
-Project and other methods