(Call for workshop proposals is now over, but is still available for a reference here)

Faces and Gestures of Human Learning (FGHL)


organizers: Jacob Whitehill, and Sidney D’Mello

The past 8 years have seen rapid growth in new technologies and services that help people learn — examples include massive open online courses (Coursera, edX, Udacity), foreign language practice software (Duolingo, Rosetta Stone), educational games, and intelligent tutoring systems (Cognitive Tutor). Contemporaneously, the near ubiquity of web cameras in personal computers, mobile phones, and tablets, as well as the proliferation of new sensors (e.g., Oculus Rift, Apple 3-D touch, Kinect) to measure high dimensional and fine-grained movements in the face, eyes, hands, and body, have opened new avenues for modeling, adapting to, and optimizing students’ emotions and behavior in a variety of different human learning contexts. In order to harness these sensing devices to track learners’ emotions and behaviors more efficiently and accurately — and in a manner that benefits learning — interdisciplinary research between computer vision, machine learning, and behavioral scientists is important to identify fruitful research directions and to make progress on concrete research questions.

Keynotes: TBA

deadline for paper submission: Feb 1, 2017

Heterogeneous Face Recognition (HFR 2017)


Organizers: Saquib Sarfraz, Rainer Stiefelhagen, Shuowen (Sean) Hu, Ben Riggan, Nathan Short

An emerging topic in face recognition is matching between heterogeneous image modalities. Coined heterogeneous face recognition (HFR), the scenario offers potential solutions to many difficult face recognition applications. Heterogeneous face recognition can involve matching between any two imaging modalities (e.g. infrared to visible, video to still images, 3D to 2D). This workshop is among the first to solicit proposals and provide a platform to bring together the face recognition community in specifically addressing the challenges and applications of heterogeneous face recognition. The workshop will serve as a venue for government & industry representatives and law enforcement agencies to interact with academics on this emerging area of biometrics research.

Keynote Speakers: Dr. Chris Boehnen, Professor Guillermo Sapiro

Deadline for Paper Submission: Feb. 2, 2017

First International Workshop on Adaptive Shot Learning for Gesture Understanding and Production (ASL4GUP 2017)


organizers : Juan Wachs, Richard Voyles, Susan Fussell, Isabelle Guyon, Sergio Escalera

In the aim of natural interaction with machines, a framework must be developed to include the adaptability humans portray to understand gestures from context, from a single observation or from multiple observations. This is also referred as adaptive shot learning – the ability to adapt the mechanism of recognition to a barely seen gesture, well-known or entirely unknown. Of particular interest to the community are zero-shot and one-shot learning, given that most work has been done in the N-shot learning scenario. The workshop aims to encourage works that focus on the way in which humans produce gestures – the kinematic and biomechanical characteristics, and the cognitive process involved when perceiving, remembering and replicating them.

Keynotes: Susan Goldin-Meadow, Philippe Schyns, and Aleix Martinez

deadline for paper submission: Feb. 1, 2017 Feb. 8, 2017 Feb 16th, 2017

Biometrics in the Wild (Bwild 2017)


Organizers: Bir Bhanu, Abdenour Hadid, Qiang Ji, Mark Nixon, Vitomir Štruc

Research on biometric recognition has long been focused on recognition from biometric data captured in ideal conditions. With recent advances in computer vision and machine learning the research focus shifted away from controlled laboratory conditions to unconstrained settings, where the variability of the captured biometric data is significantly higher and automatic recognition is a far more challenging task. Due to the countless deployment possibilities in security applications, surveillance, social media, consumer electronics or border control, biometric recognition in unconstrained settings, nowadays often referred to as »biometrics in the wild«, increasingly attracts interest from universities, government agencies as well as private companies, and represents a highly active area of research. The goal of this workshop is to present the most recent and advanced work related to biometric recognition in the wild and bring together researchers and practitioners working on problems related to unconstrained biometrics. Submitted papers should clearly demonstrate improvements over the existing state-of-the-art and use the most challenging datasets available. The workshop is interested in all parts of biometric systems ranging from detection/segmentation, landmark localization, pre-processing, and feature extraction techniques to modeling and classification approaches capable of operating on biometric data captured in the wild.

Keynote speaker: Ioannis A. Kakadiaris

Deadline for paper submission: Jan. 27, 2017 February 6th, 2017.

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