The Idiap research institute is organizing a tutorial on the BEAT platform ( https://www.beat-eu.org/platform/ ) during IEEE Seventh International Conference on Biometrics: Theory, Applications and Systems (BTAS 2015) that will be held in the September 8-11, 2015 time period in Arlington, Virginia in the Washington, DC area (USA).

Abstract

This tutorial will present the BEAT platform for online reproducible research, introducing concepts and providing an initial hands-on experience. The BEAT platform allows novice and advanced researchers to: (1) benchmark systems and components; (2) run comparative evaluations; (3) attest (certify) toolchains; (4) provide educational material for new-comers in pattern recognition and (5) optimize algorithms and systems.  All these tasks can be accomplished without installing additional software on the users computer, running exclusively from the web browser. The BEAT platform naturally enforces important research aspects such as reproducibility and component re-use.

Program:

1. • Introduction, motivation, requirements and design of the BEAT platform
   

2. • Exploring existing components at the BEAT platform
   

3. • Registered user interaction; Adding new components to the BEAT platform
   

4. • The future of the BEAT platform
   

Required prior knowledge:

The target participants for this tutorial include both beginners and advanced researchers of any computer vision field with an interest towards reproducibility, experiment longevity and software re-use. We'll examplify our system and propose a simple tutorial using face recognition - interest on this area can be a plus. Other workflows and algorithms will be shown for different tasks in image processing.

Participants shall understand the basics of programming. Knowing the Python programming language is a plus. Here is a list of resources which can be interesting:

1. • Dive into Python (free tutorial): http://www.diveintopython.net/toc/index.html
   

2. • Numerical and Scientific Programming in Python: http://www.numpy.org/, and http://www.scipy.org/
   

3. • Bob framework for Signal Processing, Machine Learning and Biometrics: https://github.com/idiap/bob/wiki/Bob-Starter-Course
   

Each participant must bring their own laptop, equipped with a modern web-browser (Google Chrome, Apple Safari or Firefox recommended) and a working internet connection to explore the platform as the tutorial flows.

Instructors

André Anjos (http://andreanjos.org) received his Ph.D. degree in signal processing from the Federal University of Rio de Janeiro in 2006. He joined the ATLAS Experiment at European Centre for Particle Physics (CERN, Switzerland) from 2001 until 2010 where he worked in the development and deployment of the Trigger and Data Acquisition systems that are nowadays powering the discovery of the Higgs boson. During his time at CERN, André studied the application of neural networks and statistical methods for particle recognition at the trigger level and developed several software components still in use today. In 2010, André joined the Biometrics Group at the Idiap Research Institute where he works mostly with face biometrics. His current interests include reproducible research in biometrics, anti-spoofing and recognition using faces, pattern recognition, image processing and machine learning.

André currently leads the design and implementation of the BEAT platform for evaluation and testing. He also serves as reviewer for several scientific journals in pattern recognition, image processing and biometrics.

Laurent El Shafey (http://www.idiap.ch/~lelshafey) received his Ph.D. in Electrical Engineering in 2014 from Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. He holds a Master in Computer Science from the TU Darmstadt, Germany and a Master in Electrical Engineering from Supelec, France.

Laurent is currently a post-doctoral researcher in the Biometric Person ecognition Group at Idiap Research Institute, Switzerland. His research interest is in machine learning and biometrics with a focus on face and speaker recognition. He is the recipient of the EAB Biometrics Research Awards 2014 (http://www.eab.org/award/hall_of_fame.html).

Sébastien Marcel received the Ph.D. degree in signal processing from Université de Rennes I in France (2000) at CNET, the research center of France Telecom (now Orange Labs). He is currently interested in pattern recognition and machine learning with a focus on biometrics.
He is a senior researcher at the Idiap Research Institute (CH), where he heads a research team and conducts research on face recognition, speaker recognition and spoofing attacks detection.
In 2010, he was appointed Visiting Associate Professor at the University of Cagliari (IT) where he taught a series of lectures in face recognition.
He is also lecturer at the Ecole Polytechnique Fédérale de Lausanne (EPFL) where he is teaching on “Fundamentals in Statistical Pattern Recognition”. He serves on the Program Committee of several scientific journals and international conferences in pattern recognition and computer vision.

He is also an Associate Editor of the IEEE Transactions on Information Forensics and  Security, a Co-editor of the “Handbook of Biometric Anti-Spoofing”, a Guest Editor of the IEEE Transactions on Information Forensics and  Security Special Issue on “Biometric Spoofing and Countermeasures”, and Co-editor of the IEEE Signal Processing Magazine  Special  Issue on “Biometric Security and Privacy”.
Finally he is the principal investigator of international research projects including MOBIO (EU FP7 Mobile Biometry), TABULA RASA (EU FP7 Trusted Biometrics under Spoofing Attacks) and BEAT (EU FP7 Biometrics Evaluation and Testing).