The following tutorials will be presented at BTAS 2016:

Morning Tutorials: 9 am to 12:30 pm

  1. Iris Recognition: Fundamentals to Future Topics
  2. Advances in Mobile and Remote Biometrics

Afternoon Tutorials: 2:00 pm to 5:30 pm

  1. Soft Biometrics: Algorithms and Applications
  2. Deep Learning for Biometrics

The details are listed below. To register for tutorials, please visit the registration link http://ieee-biometrics.org/btas2016/registration.html.

Iris Recognition: Fundamentals to Future Topics

Kevin W. Bowyer (http://www3.nd.edu/~kwb/), University of Notre Dame, USA

This tutorial will give participants an overview of how iris recognition works, the limits of common assumptions about iris recognition, and examples of nation-scale applications. Daugman-style iris recognition is taken and the reference model, but the evolution of “the” Daugman method is described and a commercial non-Daugman algorithm is described. Effects of pupil dilation difference and contact lenses are detailed. Nation-scale applications such as India’s Unique ID program and voter registration in Somaliland are presented.

Advances in Mobile and Remote Biometrics

Yunbin Deng (https://www.linkedin.com/in/yunbindeng), BAE Systems, USA

This tutorial covers the emerging technologies and applications in mobile and remote biometrics. It review the recent technology advances to mitigate the challenges in mobile and remote biometrics settings, which include unconstrained usage environment, minimum user interruption and awareness, uncooperative subjects, and the necessary of covert operation. Example technical topics are: sensor fusion in mobile authentication, realistic mobile gait authentication, and laser dropper vibrometer for standoff voice and cardiac biometrics. It also give an overview of existing sensor hardware, products, and deployment considerations for various applications of remote biometrics.

Soft Biometrics: Algorithms and Applications

Mark Nixon (http://www.ecs.soton.ac.uk/people/msn), University of Southampton, UK and Arun Ross (http://www.cse.msu.edu/~rossarun/), Michigan State University, USA

In this tutorial we will introduce the concept of soft biometrics; offer a historical perspective of the importance of these attributes; introduce a taxonomy to characterize various soft biometric traits including age, gender, ethnicity, eye/hair/skin color, body geometry, health cues, and material accessories; review algorithms that have been used to automatically extract soft biometrics from face, fingerprints, iris, gait and voice; present methods to fuse soft biometric information with primary biometric cues such as face and fingerprints; and examine the privacy and security implications of soft biometric traits.

Deep Learning for Biometrics

Mayank Vatsa (http://iab‐rubric.org/), IIIT Delhi, India and Vishal Patel (http://www.rci.rutgers.edu/~vmp93/), Rutgers University, USA

This tutorial will provide an overview of different deep learning-based methods for biometrics recognition. Specifically, we will present methods based on autoencoders, restricted Boltzmann machines and deep convolutional neural networks. We will discuss merits and drawbacks of available approaches and identify promising avenues of research in this rapidly evolving field.