Computer Vision & Graphics - COM00167M
Module summary
This module will introduce modern computer vision approaches, including discussion of the main applications and challenges.
Module will run
Occurrence | Teaching period |
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A | Spring Term 2022-23 to Summer Term 2022-23 |
Module aims
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.
Module learning outcomes
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Demonstrate a detailed understanding of the image formation process, its modelling in computer vision and its simulation in computer graphics
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Describe and implement techniques for rendering images including modelling light/material interaction
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Apply a range of methods for inferring 3D shape from images
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Apply a range of modern machine learning methods for image understanding
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Compare human and machine visual systems in the interpretation of images and graphics
Indicative assessment
Task | % of module mark |
---|---|
Online Exam -less than 24hrs (Centrally scheduled) | 100 |
Special assessment rules
None
Indicative reassessment
Task | % of module mark |
---|---|
Online Exam -less than 24hrs (Centrally scheduled) | 100 |
Module feedback
Feedback is provided through work in practical sessions, and after the final assessment as per normal University guidelines.
Indicative reading
** Forsyth and Ponce Computer Vision a Modern Approach Prentice Hall
** Anil K. Jain Fundamentals of Digital Image Processing Prentice Hall