Module Details

CE316-6-AU-CO: Computer Vision

Year: 2016/17
Department: Computer Science and Electronic Engineering
Essex credit: 15
ECTS credit: 7.5
Available to Study Abroad / Exchange Students: Yes
Full Year Module Available to Study Abroad / Exchange Students for a Single Term: No
Outside Option: No

Staff
Supervisor: Dr Adrian Clark
Teaching Staff: Dr Adrian Clark
Contact details: School Office, email:csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770

Module is taught during the following terms
Autumn Spring Summer

Module Description

Learning Outcomes

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.

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.

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

Assessment

40 per cent Coursework Mark, 60 per cent Exam Mark

Coursework

Assignment 1 weighting = 20%, submitted in wk 6, Assignment 2 weighting = 20%, submitted in wk 10.

Exam Duration and Period

2:00 during Summer Examination period.

Other information

STUDENTS SHOULD NOTE THAT THIS MODULE INFORMATION IS SUBJECT TO REVIEW AND CHANGE

Bibliography

  • Students will be supplied with a substantial set of notes that explain the techniques involved in some detail.
  • There are also excellent online references for computer vision, such as HIPR and cvonline, and online computer vision textbooks. Students will be pointed towards the relevant resources on the module website.

External Examiner Information

  • Name: DR Pandelis Kourtessis
    Institution: University of Hertfordshire
    Academic Role: Reader