Course unit details:
Computer Vision

Course unit fact file
Unit code COMP37212
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 2
Offered by Department of Computer Science
Available as a free choice unit? No

Overview

The unit aims to provide a broad introduction to Computer Vision and Image Interpretation, and  introduce the essential concepts, algorithmic tools and key applications of computer vision. This involves exploring the challenges of building practical applications in this area and discussing novel approaches to designing vision systems that can learn from data.

Pre/co-requisites

Unit title Unit code Requirement type Description
Introduction to Visual Computing COMP27112 Pre-Requisite Compulsory
Mathematical Techniques for Computer Science COMP11120 Pre-Requisite Compulsory
Students who are not from the School of Computer Science must have permission from both Computer Science and their home School to enrol.

Pre-requisites

To enrol students are required to have taken COMP11120 (waived for CM students) plus COMP27112.

Aims

The unit aims to provide a broad introduction to Computer Vision and Image Interpretation, and  introduce the essential concepts, algorithmic tools and key applications of computer vision. This involves exploring the challenges of building practical applications in this area and discussing novel approaches to designing vision systems that can learn from data.

Learning outcomes

ILO 1: Assess technologies and analyse their suitability for specific application scenarios.

ILO 2: Describe properties of image data and be able to solve problems about extraction of features and other quantitative information.

ILO 3: Design basic systems for image analysis and  computer vision and justify their design.

ILO 4: Explain the design of vision and image processing algorithms.

ILO 5: Write programs for the analysis of images, object matching and stereo vision.

ILO 6: Prepare technical reports on the evaluation of these programs on suitable test data.

Syllabus

Topics covered in the unit include:

  • Introduction to Computer Vision and digital images;
  • Essential Image processing for Computer Vision;
  • Feature-based models, Edges, Corners and local features;
  • Visual object recognition; 
  • Image retrieval;
  • Image segmentation;
  • Face detection;
  • Model-based vision; 
  • Image stitching and Panoramas;
  • Stereopsis: Recovering depth, the correspondence problem, stereo constraints.
  • Robot Vision and  Scene Reconstruction.

Teaching and learning methods

Lectures

22

Assessment methods

Method Weight
Written exam 70%
Written assignment (inc essay) 30%

Feedback methods

Written feedback is provided on 6 pieces of coursework throughout the course, corresponding to the major topics covered.

Recommended reading

Digital image processing, global edition [electronic resource]     Gonzalez, Rafael C.,    Pearson    2018    ISBN: 9781292223070

Digital image processing     Gonzalez, Rafael C.,    Pearson Education Limited    2018    ISBN: 9781292223049

Computer vision : a modern approach     Forsyth, David,    Pearson    2012    ISBN: 9781292014081

Machine vision     Jain, Ramesh (1949-)    McGraw-Hill    1995    ISBN: 0070320187

Introductory computer vision and image processing     Low, Adrian, 1956-    McGraw-Hill    1991    ISBN: 0077074033

Image processing, analysis, and machine vision     Sonka, Milan, author.    Cengage Learning    2015    ISBN: 9781133593690

Computer vision : algorithms and applications     Szeliski, Richard,    Springer    2022    ISBN: 9783030343729

Study hours

Scheduled activity hours
Lectures 23
Practical classes & workshops 8
Independent study hours
Independent study 69

Teaching staff

Staff member Role
Aphrodite Galata Unit coordinator

Fees and funding

Fees

Tuition fees for home students commencing their studies in September 2027 will be £10,050 per annum. Tuition fees for international students will be £39,700 per annum.

For general information please see the undergraduate finance pages.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Scholarships/sponsorships

The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.

For information about scholarships and bursaries please visit our  undergraduate student finance pages .

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