Postgraduate Course: Advanced Vision (INFR11151)
Course Outline
School | School of Informatics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Course type | Online Distance Learning |
Availability | Not available to visiting students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | *This course has been replaced by 'Advanced Vision INFD11002 from 2019/20*
*This course is available to distance learning students within the School of Informatics and students on the Data Science, Technology and Innovation programme.*
The main aim of the course is to give students who already have had an introduction to images and image processing a deeper understanding of the main concepts in 2D image, 3D image and video data processing. |
Course description |
This module aims to build on the introductory computer vision material taught in Introduction to Vision and Robotics. The main aim is to give students an understanding of main concepts in visual processing by constructing or analysing several vision systems during the course of the lecture series and practicals. The 6 systems are for: rigid 2D part recognition, deformable 2D part recognition, rigid 3D part recognition from stereo data, rigid 3D part recognition from range sensing, target detection and tracking in video, and video based behaviour classification.
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Course Delivery Information
Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand machine vision principles (assessed by exam).
- Acquire and process raw image data (assessed practical).
- Relate image data to 3D scene structures (assessed practical).
- Know the concepts behind and how to use several model-based object representations, and to critically compare them (assessed by exam).
- Know many of the most popularly used current computer vision techniques (assessed by exam).
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Reading List
E.R. Davies, Machine Vision - Theory, Algorithms and Practice" (Elsevier, 3rd Edition, 2005) - (Content for about 1/2 the course)
Solomon & Breckon, Fundamentals of Digital Image Processing - A Practical Approach with Examples in Matlab", Wiley-Blackwell, 2010, ISBN: 978-0470844731 (content for about 1/2 of course)
R. Szeliski, "Computer Vision", Springer, 2011, ISBN: 978-1-84882-934-3 (Content for about 1/2 of course)
T. Morris, "Computer Vision and Image Processing" (Palgrave, 1st Edition, 2004). |
Additional Information
Graduate Attributes and Skills |
The activities of the course are designed to further develop intellectual skills in the areas of: laboratory, writing (lab reports and short essays), teamwork, critical analysis, programming and laboratory skills. |
Keywords | Advanced Vision,Distance Learning |
Contacts
Course organiser | Dr Robert Fisher
Tel: (0131 6)51 3441
Email: |
Course secretary | Mrs Sam Stewart
Tel: (0131 6)51 3266
Email: |
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