Course title / code
Computer Vision and Applications (CI5336701)
Credits
Graduate level / 3 credits
English lecture (EMI)
Course objectives
We focus on the contents from digital cameras for generating 3D spatial information using computer algorithms. This course emphasizes the computation of 3D information from 2D images, such as 3D scanning, SLAM (Simultaneous Localization and Mapping), image synthesis, and other 3D applications. It aims to enhance students’ skills in computing images, which can be applied in interactive, measurement, artificial intelligence, monitoring, and other related 3D fields.
Outline of lectures
This course will discuss about the principle and technology of “Computer Vision” research field. Applications on Stereo / Multiview / Augmented Reality are also revealed, and this course outline includes,
- Pin-hole camera
- Projective 2D geometry
- Camera Models
- Projective 3D geometry
- Camera Calibration
- Epipolar geometry
- Multiview and 3D reconstruction
- Applications on stereo vision
- Applications on augmented reality
Textbooks
Professor will provide slides which are from references and research papers.
References
“Multiple View Geometry in Computer Vision,” Richard Hartley and Andrew Zisserman, 2nd Edition Cambridge University Press. 2004. (ISBN: 0521540518) In Sec.2~5,6, Sec.7~11, Sec.13~15.
“Computer Vision, A Modern Approach,” David A. Forsyth and Jean Ponce, Prentice Hall. In Sec.1, 2, 3,10~13. (main), Sec.14~15 (select).
Note
You should have the ability of writing programs for solving problems. All assignments will need the skill. However, beginners in programming are also welcome to enroll.
The theoretical aspects of the course may be challenging, and most assignments do not have standard answers, requiring creative problem-solving. Before choosing to enroll, please assess your own course workload capacity.
Grading
Participation, feedback(10%)
Homework assignments (40%)
Midterm project (25%)
Final project (25%)
* the proportion will be confirmed after 1st week of the semester
Prerequisites
It is recommended that you have taken courses in engineering mathematics or linear algebra, particularly in knowing matrix operations, as this course extensively utilizes matrix operations
Misc.
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