Module Information

Module Identifier
CS34110
Module Title
Computer Vision
Academic Year
2017/2018
Co-ordinator
Semester
Semester 1
Pre-Requisite
Reading List
External Examiners
  • Dr Hong Wei (Associate Professor - University of Reading)
  • Dr John Hunt (Chief Operating Officer - Mallon Associates International)
 
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 20 x 1 Hour Lectures
Workshop 2 x 2 Hour Workshops
 

Assessment

Assessment Type Assessment length / details Proportion
Semester Exam 2 Hours   Written Exam  100%
Supplementary Exam 2 Hours   Supplementary Exam  Will take the same form, under the terms of the Department's policy.  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Express a consolidated and extended understanding and knowledge of Computer Vision techniques.

2. Compare, critically evaluate and discuss competing methods.

3. Explain the problems, techniques and difficulties associated with the different areas of Computer Vision.

Brief description

The module will introduce the subject of Computer Vision in the context of robotics, in particular mobile and industrial robotics. It will start with low-level vision such as edge detection, feature detection, and segmentation. Intermediate vision will describe various techniques to infer 3 dimensional information from images. Some high-level techniques will be introduced

Content

Foundations of vision: Image acquisition, sources of noise, human visual perception, and the evaluation and design of visual computing systems.

Edges and features: The image as landscape, edge detection, feature detection and representation, appearance as feature.

Motion: The video as a 3D dataset, feature tracking, background subtraction, modelling motion and change.

Objects: Grouping features, grouping motion, modelling variability. Learning models.

3D: Shape from X (shading, defocus, occlusion, photometric stereo). Multiview techniques (binocular, structure from motion). Direct 3D capture techniques (lidar, sonar).

Module Skills

Skills Type Skills details
Application of Number Computer vision involves higher level mathematical concepts
Communication Exam writing develops written communication skills
Improving own Learning and Performance Independent learning is necessary to complete the module
Information Technology Information and communications technology is intrinsic to computer science.
Personal Development and Career planning There is a substantial demand for computer vision expertise.
Problem solving Problem solving is intrinsic to computing in general.
Research skills This is a research driven module; research skills will be exercised throughout
Subject Specific Skills Computer vision.
Team work This module will require individual rather than team work.

Notes

This module is at CQFW Level 6