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Dublin University Crest Computer Science Department > Department Details > Personnel > Dr. Kenneth Dawson-Howe Trinity College Crest
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Organisation of CSU44053 Computer Vision 2022-23

All course material is on the College e-Learning environment (Blackboard). Please go to once you are enrolled in this course.

For those considering switching to this option the expected module organisation details will be provided here along with links to the course material.


  • Current plan for CSU44053 [1st July 2022]: (Subject to change) Based on current information I expect that we will be teaching in person in the coming year. We are going to use something called 'the flipped classroom' where students have to study material (pre-recorded lectures) before class and we will then discuss and make use of this material in our in person sessions.
    • In the first week there will be two live lectures introducing the area of Computer Vision, talking about some sample applications and discussing the organisation, goals and content of the module. There will also be one or two prerecorded lecture sessions. Students should spend time during this week installing Visual Studio (version 2019 is recommended in 2022-23 but this may well change depending on what version our Support Staff install on the lab machines!), OpenCV (version 4.5.3 is recommended in 2022-23 - again subject to change) & TIPS (although please note that a new version will be issued around the start of the semester which will provide support Assignment 1), and should spend time familiarising themselves with the software. You should do the Introductory Lab which is in the "Assignments and Labs" content area (in the menu on the left hand side in Blackboard).
    • In normal weeks there will be
      • Around 4 prerecorded lecture sessions (15-25 minutes long) will be provided along with mini tests associated with the topics to try to ensure that the material is understood. These are graded AND must be done before the live weekly sessions (or 0 marks are awarded). All students must complete the weekly lecture material and mini-tests before the deadline (which is set before the Q&A session).
      • Weekly Q&A discussion & Advanced Topics: Questions about the lecture material just covered will be discussed with the whole class. We will also hopefully spend some time looking at more advanced topics in Vision (such as text recognition, face recognition, head pose estimation, machine learning).
      • Tutorial sessions. In the tutorials, application problems will be presented to the class and groups of (3-4) students will try to come up with a solution (based on the techniques covered so far in the module). After around 10 minutes, different groups will present their solutions which we will discuss. We typically deal with 2 problems in a tutorial.
    • In the last week there will be two live lectures to review course materials and look at exam issues.
    • A Discussion Board is provided for the module where issues can be raised and discussed amongst the class. The discussion board is broken into a number of "forums" and all members of the class can post new threads within these forums or add comments to existing threads. All posts must be respectful of all other participants, and no hurtful / rude / racist / etc posts should ever be made.
  • Assessment:
    • 10% Mini tests. These are very small tests which ask questions relating to the lecture material, each of which should only take a few minutes to complete. You may only submit each test once. Each week the test(s)s have to be done before the scheduled Q&A session to get any marks.
    • 40% Assignments. There will be 2 assignments during the semester. The first will be a programming assignment counting for 30% where students must develop a solution to a series of related practical problems (which will be released in 5 separate parts before reading week) and write a report. The second will be an exam style question (or questions) counting for 10%.
    • 50% Time limited take home exam.

Links for material (including pre-recorded sessions):

Email  Kenneth.Dawson-Howe @