This course covers a theory and fundamental problems in computer and robot vision. The techniques will be showcased using practical applications.
Your grade in the course depends on the result of the following assessments:
Assignment 1: 20%
Midterm Test: 20%. 1st November 2023, 9:00 - 12:00 Taiwan Time. Midterm is open book and open Internet and will be administered via Discord channel: https://discord.gg/V6dR8TYU
Assignment 2: 20%
Final Exam: 40%
A list of lecture slides is available in the chat server
Assignment 1 (Deadline: 25th Oct 2023): Assignment - Projection Magic
The following are links to the [Jupyter notebooks] (https://drive.google.com/drive/folders/1BRNqiFcAJDvpgTtvfX4Dy-tikhrYxB51?usp=sharing) that we used in class.
The notebooks can be run on Google colaboratory or you can download them and run them on your own machine/server.
Some of the classes will be conducted online using the following setup.
The course will use the following Discord server to support discussions.
Make sure that you pay attention to the messages on the server. Links to additional course material, assignments, and tests will be posted on discord only. https://discord.gg/rRHmqjpc.
I will use research papers describing both the background material as well as the current state of the art. Students are expected to understand the material as well as being able to implement simple versions of the described algorithm.
The course uses Computer Vision: Algorithms and Applications by Richard Szeliski as additional teaching material. You can download a free copy of the book from the authors website.
Students are reminded that there are penalties for academic dishonesty. Academic dishonesty includes submitting assignments that are not entirely the student’s own work. A declaration sheet, which states that the work being submitted is completely your own, is available here honesty declaration. This sheet must be filled out and attached to all assignments or projects, which you are submitting as part of your class work. No assignment or project will be marked unless the declaration is attached.
It is your responsibility to ensure that you are entitled to be registered in this course. If you are not entitled to be in this course, you will be withdrawn, or the course may not be used in your degree program. There will be no fee adjustment. This is not appealable. Please be sure to read the course description for this and every course in which you are registered.
Should major disruptions to university activities occur as a result of a pandemic, the course content, marks breakdown, and other provisions of this document may be adjusted as the circumstances warrant.