Learning objectives
The course aims to provide the knowledge necessary for the design and application of artificial vision systems, promoting the acquisition of design skills that can also be directly used in a work environment. The course includes the presentation of basic methodological notions, the development of advanced topics also through specific seminars, and the carrying out of mandatory individual laboratory exercises. To carry out the laboratory activities, students must have software development skills, mainly in a C/Linux/OpenCV environment.
Prerequisites
Artificial Vision requires practical knowledge of the topics covered in the courses of Electronic Calculators, Fundamentals of Computer Science, and Operating Systems. For the development of the projects, the C/C++ language will be used with the help of the OpenCV library.
Course unit content
Fundamental algorithms and concepts of Computer Vision:
01. images and images format
02. cameras
03. local processing
04. point processing
05. binary images
06. lines and edges
07. camera models
09. camera calibration
09. monocular reconstruction
10. epipolar geometyry
11. stereo vision
12. model fitting
13. features extraction
14. features matching
15. styructure from motion and segmentation
16. OpenCV
Full programme
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Bibliography
D. A. Forsyth and J. Ponce. Computer Vision: A Modern Approach (2nd Edition). Prentice Hall, 2011.
R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, 2003.
Teaching methods
Both theory lessons and OpenCV tests on personal laptop
Assessment methods and criteria
SCORE
- written essay on THEORY topics, 2 hours, 15 POINTS (minimum 6)
- laboratory test using personal laptop, 2 hours, 15 POINTS (minimum 8)
- optional assigbnements in the laboratory, 2 POINTS
VALIDITY'
Theory test, practice test and assignments remain valid until the autumn session.
WRITTEN TEST MODE
2-3 open-ended questions on theory topics.
It is not allowed to consult notes or manuals.
PRACTICAL TEST MODE
Write a C/C++ program similar to the ones seen during laboratory lessons:
- it will take place in the laboratory
- the use of personal laptops is permitted
- you are allowed to use any type of material and OFFLINE code: notes, sample code, exercises, manuals, assignments and other code that you have written.
- It is NOT allowed to consult online sites during the test
it will be evaluated even if the code compiles and terminates correctly (no crashes or various segmentation faults)
Other information
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2030 agenda goals for sustainable development
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