Image-based Biometrics

Content of this course is based on principles of computer vision that represent a basis for the majority of biometric systems, where the input is an image. As a part of this course, the content will be delivered theoretically and practically through use-cases and the state-of-the-art implementations, including deep learning.

Aims of the course

To present biometrics from the basics, right to the smallest details in implementations and state-of-the-art research.

Why should you attend this course?

To learn about the all-important field of biometrics and get advice on your specific biometric-related challenges.

After the course, you will:

• know the key properties of each biometric modality,
• understand all the steps of each biometric system,
• know to define needed properties to introduce a biometric system into a real-life environment,
• know how to properly measure and compare the performance of biometric systems,
• understand the key terminology of each modality and the use of it in the real-life systems,
• understand the advantages and shortcomings of specific modalities,
• know how to fuse modalities to achieve better performance of biometric systems,
• know key algorithms of computer vision in biometrics.