ELEN0016 Computer Vision

Information

• All information about the course, including the slides, can be found on the University website.

• Note that specific slides will be added for certain lectures, please check the class schedule for updated slides.

Class schedule

• Session 1 (16/09/26): General Information. 

  • • • • Part 1. Introduction, color spaces, acquisition.  Following the course slides

        • Part 2. Filtering + hands-on with a Jupyter notebook. slides and TP ; some solutions

• Session 2 (24/09/26): Camera models and camera calibration.

  • • • • Part 1. Camera models. Download slides

        • Part 2. Camera calibration + hand-on with a Jupyter notebook. Download slides and download resources

• Session 3 (30/09/26): Motion detection by background subtraction and image segmentation.

  • • • • Part 1. Motion detection by background subtraction. Following the course slides

        • Part 2. Image segmentation. + TP on background subtraction. Following the course slides +  exercises + data

• Session 4 (08/10/25): Mathematical morphology, grayscale morphology, and non-linear filtering.

  • • • • Part 1. Following the course slides. Download slides. 

        • Part 2. Hands-on. Download resources.

• Session 5 (15/10/25): 3D reconstruction (part 1), segmentation, and motion detection.

  • • • • Part 1. 3D reconstruction (slides) and segmentation. Following the course slides

        • Part 2. Motion detection. + TP motion detection. Following the course slides +  exercises

• Session 6 (22/10/25): 3D reconstruction (part 2), introduction to machine learning for computer vision.

  • • • • Part 1. 3D reconstruction +hands-on with a Jupyter notebook. Download slides and download resources 

        • Part 2. Introduction to machine learning for computer vision. Download slides 

• Session 7 (05/11/25): Deep learning for computer vision

  • • • • Part 1. Computer vision and basics of artificial intelligence. Download slides

        • Part 2. Deep learning building blocks and architectures. Download slides

• Session 8 (12/11/25): Performance analysis, TP on fundamentals of deep learning for computer vision

  • • • • Part 1. Performance analysis. Download slides

        • Part 2. TP on fundamentals of deep learning for computer vision. Download resources

• Session 9 (19/11/25): Human pose estimation, project Q&A

  • • • • Part 1. Human pose estimation Download slides

        • Part 2. Project Q&A