SGN-45007 Computer Vision, 5 cr
Additional information
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
Person responsible
Esa Rahtu
Lessons
| Implementation | Period | Person responsible | Requirements |
| SGN-45007 2019-01 | 3 |
Esa Rahtu |
Learning Outcomes
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
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Image formation | ||
| 2. | Image processing | ||
| 3. | Feature detection & matching | ||
| 4. | Feature based alignment & image stitching | ||
| 5. | Dense motion estimation | ||
| 6. | Structure from motion | ||
| 7. | Stereo and 3D reconstruction | ||
| 8. | Recognition |
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.
Assessment scale:
Numerical evaluation scale (0-5)
Partial passing:
Additional information about prerequisites
Programming skills and basic knowledge of data structures and mathematics (linear algebra, probability) will be necessary.
Correspondence of content
| Course | Corresponds course | Description |
| SGN-45007 Computer Vision, 5 cr | SGN-45006 Fundamentals of Robot Vision, 5 cr |