This module will introduce modern computer vision approaches, including discussion of the main applications and challenges.
Occurrence | Teaching period |
---|---|
A | Semester 1 2024-25 |
This module will introduce modern computer vision approaches, including discussion of the main applications and challenges. It will cover issues of image formation, camera geometry, feature detection, motion estimation and tracking, image classification and scene understanding, using a range of model-based approaches.
Demonstrate a detailed understanding of the image formation process, its modelling in computer vision and its simulation in computer graphics
Describe and implement techniques for rendering images including modelling light/material interaction
Understand a range of methods for inferring 3D shape from images
Apply fundamental machine learning methods for image understanding
Task | % of module mark |
---|---|
Closed/in-person Exam (Centrally scheduled) | 100 |
None
Task | % of module mark |
---|---|
Closed/in-person Exam (Centrally scheduled) | 100 |
Feedback is provided through work in practical sessions, and after the final assessment as per normal University guidelines.
** Forsyth and Ponce Computer Vision a Modern Approach Prentice Hall
** Anil K. Jain Fundamentals of Digital Image Processing Prentice Hall