CE316-6-SP-CO:
Computer Vision

The details
2023/24
Computer Science and Electronic Engineering (School of)
Colchester Campus
Spring
Undergraduate: Level 6
Current
Monday 15 January 2024
Friday 22 March 2024
15
17 June 2022

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

BENGH615 Robotic Engineering,
BENGH616 Robotic Engineering (Including Year Abroad),
BENGH617 Robotic Engineering (Including Placement Year),
BENGH618 Robotic Engineering (Including Foundation Year),
BSC H717 Robotics,
BSC H718 Robotics (including Placement Year),
BSC H719 Robotics (including Year Abroad),
BSC I400 Artificial Intelligence,
BSC I401 Artificial Intelligence (Including Foundation Year),
BSC I402 Artificial Intelligence (including Placement Year),
BSC I403 Artificial Intelligence (including Year Abroad)

Module description

This module provides an understanding of the principles and main methods for computer vision, and with practical experience of solving simple computer vision tasks. The principles and main methods of computer vision will be explained along with examples of visual data and how some methods facilate aspects of two/three-dimensional vision. Students will write computer programs to solve vision tasks.

Module aims

The aim of this module is to provide students with an understanding of the principles and main methods for computer vision, and with practical experience of solving simple computer vision tasks.

Module learning outcomes

After completing this module, students will be expected to be able to:

1. Describe the principles and main methods for computer vision.
2. Explain, on examples of visual data, how some methods facilitate aspects of two-dimensional vision.
3. Explain, on examples of visual data, how some methods facilitate aspects of three- dimensional vision.
4. Write computer programs to solve simple vision tasks.

Module information

Outline Syllabus

Image formation, image enhancement and filtering, colour representations, edge detection, corner detection, circle detection, region growing, image segmentation, features and object recognition. Faces.

Stereopsis and depth reconstruction, target tracking, statistical shape models, computer vision system evaluation.

Learning and teaching methods

Lectures and Laboratories

Bibliography

This module does not appear to have any essential texts. To see non - essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Progress Test 1    50% 
Coursework   Progress Test 2     50% 
Exam  Main exam: In-Person, Open Book (Restricted), 120 minutes during Early Exams 
Exam  Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period) 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
40% 60%

Reassessment

Coursework Exam
40% 60%
Module supervisor and teaching staff
Dr Adrian Clark, email: alien@essex.ac.uk.
Dr Adrian Clark
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770

 

Availability
Yes
No
Yes

External examiner

Dr Shadan Khan Khattak
Cardiff Metropolitan University
Senior Lecturer
Resources
Available via Moodle
Of 77 hours, 10 (13%) hours available to students:
66 hours not recorded due to service coverage or fault;
1 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information

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