Module Descriptor School of Computer Science and Statistics
|Module Name||Computer Vision|
|Module Short Title||N/a|
|Semester Taught||First semester|
|Contact Hours||Lecture hours: 23 hours|
Lab hours: 1 hour
Tutorial hours: 9 hours
Total hours: 33 hours
|Module Personnel||Dr. Kenneth Dawson-Howe|
When students have successfully completed this module they should be able to:
The aim of this module is to give students a firm understanding of the theory underlying the processing and interpretation of visual information and the ability to apply that understanding to ubiquitous computing and entertainment related problems. It provides them with an opportunity to apply their problem-solving skills to an area which, while it is firmly part of computer science/engineering, draws strongly from other disciplines (physics, optics, psychology). The module is based around problems so that the technology is always presented in context and during some tutorials students work in groups to design solutions to real world problems using the techniques that they have been taught. In addition, the module has a significant practical component so that students can appreciate how difficult it can be to apply the technology.
Specific topics addressed in this module include:
Topics will change a little bit from year to year.
|Recommended Reading List|
A Practical Introduction to Computer Vision with OpenCV, by Kenneth Dawson-Howe, Wiley, May 2014.
|Module Prerequisites||A working knowledge of C++|
The labs and assignments account for 20% of the final mark and the exam 80%. Students must answer 2 out of 3 exam questions. There is no supplemental examination in this subject.
|Academic Year of Data|