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MEng Software Engineering

Year of entry: 2020

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Course unit details:
Introduction to Visual Computing

Unit code COMP27112
Credit rating 10
Unit level Level 2
Teaching period(s) Semester 2
Offered by Department of Computer Science
Available as a free choice unit? Yes

Overview

Visual Computing brings together two fundamentally important aspects of modern computing: Computer Graphics - concerned with the synthesis of images from computer models - and Image Processing, which deals with analysis and understanding of images by computers. There are now considerable overlaps between these two, traditionally separate, fields of research and their applications.
The Visual Computing theme consists of the following course units:
Year 2: Computer Graphics and Image Processing (10 credits)
Year 3: Advanced Computer Graphics (10 credits)
Year 3: Computer Vision (10 credits)
 

Pre/co-requisites

Students who are not from the School of Computer Science must have permission from both Computer Science and their home School to enrol.

Aims

The importance of visual interfaces has never been greater. Graphical interfaces have become ubiquitous, from desk-top interaction, to games and three-dimensional virtual environments. In parallel, there has been an explosion in digital image processing and analysis. We take for granted digital photography and video, while our health services rely on digital X-ray systems, CT and MRI scanners for seeing inside our bodies. Meanwhile, the visualization of computer simulations is an essential aspect of product design and testing, genome exploration, drug design, and climate modelling. The demand for computer scientists with advanced knowledge of such areas has never been greater.

The theme will enhance your knowledge and understanding, answering such questions as:

  • How are three-dimensional environments represented in a computer, and how are interactive 3D worlds created?
  • How are 2D and 3D representations combined ? for example, how can we recover 3D geometry from 2D images?
  • How are the basic mathematical techniques and algorithms used to build useful applications?
  • How are images stored, processed and manipulated?
  • How can computers interpret images captured by cameras and other recording devices?

Learning outcomes

  • Describe the principles of interactive computer graphics

  • Design systems using fixed-pipeline OpenGL

  • Apply the mathematics of 3D transformations and viewing

  • Describe the principles of the rendering pipeline

  • Describe the principles of image processing

  • Implement fundamental image processing algorithms

Syllabus

Fundamentals (1 week)
2 and 3 D Coordinate systems. Vectors, matrices and basic vector/matrix operations. 2 and 3D geometric transformations (translation, rotation, scaling, affine).
 
3D Modelling and Illumination (5 weeks)
The programmable graphics pipeline. 3D graphics primitives, meshes, models, and scene graphs. Rasterisation and hidden surface removal. The camera model, viewing and projection. Local illumination: ambient, diffuse, specular. Gouraud and Phong shading. Writing shaders with GLSL. Surface detail: textures, bump mapping.
 
Image Transformations (2 weeks)
Image representations: resolution, colour models. Image transformations: point transformations (windowing, histogram equalisation, colour transformations and colour spaces).
 
Image Enhancement (3 weeks)
Local processes, convolution, image smoothing (local averaging, weighted averaging), size of support, Gaussian mask. Edge enhancement (unsharp masking). Edge detection (Prewitt, Sobel, Canny, Marr-Hildreth, Hough), Thresholding, blob detection, simple measurement (geometric features).  Rank order filters (median, max-min
 

Teaching and learning methods

Lectures

24 hours spread over 12 weeks

Examples classes

5 hours of assessed, self-study Coursework Assignments.

Laboratories

10 hours in total, 5 2-hour sessions.

Three.js laboratory exercises. 
C Programming, manipulating images and finding objects using OpenCV.
Self-paced Coursework Assignments using example programs and software tools (with a small amount of experiment-driven programming). Simple OpenCV familiarisation exercises.
 

Employability skills

Analytical skills
Innovation/creativity
Project management
Problem solving

Assessment methods

Method Weight
Written exam 70%
Written assignment (inc essay) 5%
Practical skills assessment 25%

Feedback methods

Face to face feedback and marking  in programming laboratories.

Three.js laboratory exercises. 
C Programming, manipulating images and finding objects using OpenCV.
Self-paced Coursework Assignments using example programs and software tools (with a small amount of experiment-driven programming). Simple OpenCV familiarisation exercises.
 

Recommended reading

COMP27112 reading list can be found on the Department of Computer Science website for current students.

Study hours

Scheduled activity hours
Assessment written exam 2
Lectures 24
Practical classes & workshops 10
Independent study hours
Independent study 64

Teaching staff

Staff member Role
David Morris Unit coordinator

Additional notes

Course unit materials

Links to course unit teaching materials can be found on the School of Computer Science website for current students.

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