Biometrics like any applied pattern recognition and machine learning research contains experimental results on real-world data. Results are typically summarized as a set of tables and figures, allowing the comparison of various methods. Unfortunately, result reproducibility is often an overlooked feature of original research publications, competitions, or benchmark evaluations. The main reason for such a gap is the complexity on the development of software associated with these reports. Software frameworks are difficult to install, maintain, and distribute, while scientific experiments often consist of many steps and parameters that are difficult to report. The increasingly rising complexity of research challenges make it even more difficult to reproduce experiments and results. As a consequence it is foremost importance to promote any actions towards reproducible research such as sharing Open Source software.
For the last seventeen years, the International Summer School on Biometrics has been closely following the developments in science and technology to offer a cutting edge, intensive training course, always up to date with the current state-of-the-art.