SGN-45006 Fundamentals of Robot Vision, 5 cr
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 is only intended for degree students
||Accepted exercises and final exam|
Students will learn - Image formation and image processing - Feature extractions - Object detection and tracking - Use of multiple images - Mapping, visual reconstruction, VR, AR - SLAM - Deep NN
|Content||Core content||Complementary knowledge||Specialist knowledge|
|3.||Feature detection & matching|
|4.||Feature based alignment & image stitching|
|5.||Dense motion estimation|
|6.||Structure from motion|
|7.||Stereo and 3D reconstruction|
Instructions for students on how to achieve the learning outcomes
You must actively participate the lectures and do the exercises. In particular, familiarize yourself with the exercise questions before the exercise session.
Numerical evaluation scale (0-5)
|Type||Name||Author||ISBN||URL||Additional information||Examination material|
|Book||Computer Vision: Algorithms and Applications||Richard Szeliski||Main course book (freely available online)||No|
Additional information about prerequisites
Programming skills and basic knowledge of data structures and mathematics (linear algebra, probability) will be necessary.
Correspondence of content
|SGN-45006 Fundamentals of Robot Vision, 5 cr||IHA-4406 Fundamentals of Robot Vision, 5 cr|
|SGN-45006 Fundamentals of Robot Vision, 5 cr||SGN-45007 Computer Vision, 5 cr|