Computer Vision & Graphics - COM00167M

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  • Department: Computer Science
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2022-23

Module summary

This module will introduce modern computer vision approaches, including discussion of the main applications and challenges.

Module will run

Occurrence Teaching period
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

  • 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

  • Apply a range of methods for inferring 3D shape from images

  • Apply a range of modern machine learning methods for image understanding

  • 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