CS3VI18-Visual Intelligence

Module Provider: School of Mathematical, Physical and Computational Sciences
Number of credits: 10 [5 ECTS credits]
Level:6
Terms in which taught: Spring term module
Pre-requisites: CS1MA16 Mathematics for Computer Science or CS1MA20 Mathematics and Computation or CS1MA20NU Mathematics and Computation or MA1LA Linear Algebra
Non-modular pre-requisites:
Co-requisites: CS3IA16 Image Analysis
Modules excluded:
Current from: 2023/4

Module Convenor: Prof James Ferryman
Email: j.m.ferryman@reading.ac.uk

Type of module:

Summary module description:

This module covers the topics of visual perception and computer vision.

Aims:

This module aims to provide students with an appreciation of human cognitive abilities in visual perception, fundamental knowledge in high level computer vision, and examples of application areas including video surveillance.

This module also encourages students to develop a set of professional skills, such as problem solving, critical analysis of published literature, creativity, technical report writing for technical and non-technical audiences, self-reflection and effective use of commercial software.

Assessable learning outcomes:

Students who complete this module will have:

• basic knowledge of human perceptual skills relating to vision;


• the ability to address high level issues relating to computer vision including pattern classification, knowledge of geometric-based vision and appearance-based vision;


• knowledge of application of computer vision including generic object recognition, cognitive computer vision and computational visual surveillance.

Additional outcomes:

Improved programming skills and applied computer vision through practical work.

Outline content:

The module includes the following: introduction to natural vision (human perception); theory of image-based pattern classification; geometric-based vision; appearance-based vision; object recognition; applications of computer vision.

Brief description of teaching and learning methods:

Lectures supported by laboratory practicals, tutorials and a coursework assignment (project).