Course Details in 2027/28 Session


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Module Title LH Computer Vision and Imaging
SchoolComputer Science
Department Computer Science
Module Code 06 30213
Module Lead Jianbo Jiao
Level Honours Level
Credits 20
Semester Semester 1
Pre-requisites LC Mathematical Foundations of Computer Science - (06 30181) LC Data Structure & Algorithms - (06 30175)
Co-requisites
Restrictions None
Contact Hours Lecture-33 hours
Practical Classes and workshops-22 hours
Guided independent study-145 hours
Total: 200 hours
Exclusions
Description Vision is one of the major senses that enables humans to act (and interact) in (ever)changing environments, and imaging is the means by which we record visual information in a form suitable for computational processing. Together, imaging and computer vision play an important role in a wide range of intelligent systems, from advanced microscopy techniques to autonomous vehicles. This module will focus on the fundamental computational principles that enable an array of picture elements, acquired by one of a multitude of imaging technologies, to be converted into structural and semantic entities necessary to understand the content of images and to accomplish various perceptual tasks. We will study the problems of image formation, low level image processing, object recognition, categorisation, segmentation, registration, stereo vision, motion analysis, tracking and active vision. The lectures will be accompanied by a series of exercises in which these computational models will be designed, implemented and tested in real-world scenarios.
Learning Outcomes By the end of the module students should be able to:
  • Understand the main computer vision and imaging methods and computational models
  • Design, implement and test computer vision and imaging algorithms
  • Know how to synthesise combinations of imaging and vision techniques to solve real-world problems
Assessment 30213-01 : Examination : Exam (Centrally Timetabled) - Written Unseen (50%)
30213-02 : Continuous Assessment : Coursework (50%)
Assessment Methods & Exceptions Assessment:
Examination (50%),
Continuous Assessment (50%)

Reassessment:
Examination (100%)
Other Birmingham version of Dubai based module 32578
Reading List