See Specialisations

Computer Vision and Biometrics

CHAIR: DMB (Data Management and Biometrics)

Introduction

Computer Vision includes methods for acquiring, processing, analysis of, and understanding images or image sequences from the real world in order to produce information, e.g., in the form of decisions. It is the combination of Image Processing and Statistical Pattern Recognition. Biometrics deals with the recognition of persons based on physiological characteristics, such as face, fingerprint, vascular pattern or iris, and behavioural traits, such as gait or speech. It combines Computer Vision with knowledge of human physiology and behaviour.

In the Biometric Pattern Recognition LAB of the Data Science group, we research Computer Vision and Biometrics and their applications. The research of the group is both fundamental and application oriented; we develop new theoretical concepts, such as new methods for combining classifiers, as well as technology for practical applications. Current research topics are for example face recognition at a distance, intelligent video surveillance, biometrics for border control, finger vein recognition, 3D face modelling and recognition, deep learning, forensic biometrics and detection of manipulation of photographs or videos. One of our main drivers is to develop explainable methods, not just methods that work, but methods that also contribute to understanding processes. Our research is embedded in the Digital Society Institute.

Programme mentor

dr.ir. L.J. Spreeuwers (Luuk)
Associate Professor

Compulsory courses

Code

Course

Study load (EC)

Quarter

201600070

Machine Learning I

5

1A

201500040

Introduction to Biometrics 3TU

5

1B

201900007

Perspectives on Engineering Design

2,5

1B

201100137

Philosophy of Engineering: Ethics

2,5

1B

191210910

Image Processing and Computer Vision

5

2A

201100254

Advanced Computer Vision and Pattern Recognition

5

2B

Safe choices for your electives

Computer Vision & Biometrics has defined a complete programme with preferred courses. Of course you may propose other courses, but the programme below is a safe choice.

Code

Q1A:

EC

201600070

Machine Learning I

5

191506103

Statistics and Probability

5

201600074

Natural Language Processing

5

Q1B:

201500040

Introduction to Biometrics 3TU

5

201600071

Machine Learning II or:


5


201800177

Deep Learning From Theory to Practice or:

191210920

Optimal Estimation in Dynamic Systems

201900007

Perspectives on Engineering Design

2,5

201100137

Philosophy of Engineering: Ethics

2,5

Q2A:

191210910

Image Processing and Computer Vision

5

191551200

Scientific Computing

5

Q2B:

201100254

Advanced Computer Vision and Pattern Recognition

5

201500042

Privacy-Enhancing Technologies

5


Also, there is a capita selecta course:

201800419

Capita Selecta Computer Vision and Biometrics

2 to 6EC

Website for more information

https://www.utwente.nl/en/eemcs/ds/