Module overview
Biometrics is about how we can recognise people automatically, by personal characteristic. We all have fingerprints and faces - and they are unique. We have to sense the information, process it and then deliver an assessment of the identity associated with that data. That's what this course is about: it's about electronics, computer science, maths, and pattern recognition. It assumes you have numerate skills, and can program a computer in some way. The course does rely much on computer vision, as most biometrics technologies are based on computer vision. Some grounding in this will be part of the course. You might choose to take this course if you are interested in cutting edge technology, much of which is still in a research stage, which whilst benefitting, even challenges the way society operates. The course will be given by Mark Nixon who has been involved in biometrics from its infancy, and who has pioneered biometrics technologies (gait, ear and soft...... yes "soft"), all at Southampton. The course has evolved from many professional courses, professional tutorials (IEEE/IAPR etc) and from the many keynote/ plenary lectures that I (Mark) have given over the years. The course will be challenging, but also should be a very interesting and enjoyable introduction to an area of topical interest worldwide.
Aims and Objectives
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- The current performance limitations of biometrics systems
- The range of biometric technologies and their advantages and disadvantages
- The newest approaches to biometrics and how they fit in its technological landscape
- The principles of identity analysis and its history
- How biometrics systems operate from sensor to decision
Syllabus
- Introduction to biometrics.
- Applications of biometrics.
- Overview of computer vision methods.
- Computer vision and image processing.
- Automated analysis of computer images.
- Face and fingerprint biometrics.
- Holistic and model-based approaches.
- Identification through the ages: history of biometrics and (forensic) identification.
- Gait biometrics, recognition by walking and running.
- Iris recognition, iris image acquisition and processing.
- Performance limits and performance evaluation.
- Moving object recognition and description.
- Applications of computer vision-based recognition.
- From images to measurements.
- Demonstration. How do biometrics systems really work? Can we recognise people?
- New modalities and current research. Performance limits, and how will they be resolved.
Learning and Teaching
| Type | Hours |
|---|---|
| Revision | 10 |
| Follow-up work | 18 |
| Lecture | 36 |
| Tutorial | 12 |
| Wider reading or practice | 42 |
| Completion of assessment task | 14 |
| Preparation for scheduled sessions | 18 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Anil K. Jain, Patrick Flynn, and Arun A. Ross (2008). Handbook of Biometrics. Springer.
Mark Nixon and Alberto Aguodo (2012). Feature Extraction and Image Processing for Computer Vision. Academic Press.
Mark Nixon, Tieniu Tan and Rama Chellappa (2006). Human Identification Based on Gait. Springer.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Final Assessment | 70% |
| Continuous Assessment | 30% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Set Task | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Set Task | 100% |
Repeat Information
Repeat type: Internal & External