Submission Deadline: 1 August 2017
I. Aim and Scope
Automatic Facial Action Coding, in particular FACS Action Unit coding, has continued to see steady progress since the first challenge in automatic facial expression recognition was held (FERA 2011). Two more FACS challenges have been organised since then (FERA 2015 and 2017), which opened benchmarking to interactive scenarios using the SEMAINE database, and to spontaneous emotions and non-frontal head-poses using the BP4D database. Other benchmarking databases have also been widely used, e.g. the DISFA or UNBC-McMaster shoulder-pain expression archive database.
We are calling for papers in the broad area of facial action coding, with a stated interest in and focus on fair comparison on aspects of occurrence and intensity estimation accuracy, computational complexity, robustness to the prevailing challenging conditions, and reproducibility of results. All submissions *must* report on the three FERA testsets (2011, 2015, and 2017), in addition to any other data sets authors wish to report on. Results on the FERA testsets will be included in a summary of the special issue.
Papers are invited addressing any of the following themes:
Action Unit Occurrence detection
Action Unit intensity estimation
FACS analysis for human behaviour interpretation
FACS analysis under challenging conditions
Deep Learning for Automatic Facial Coding
Multimodal and multi-cue behaviour analysis using FACS
Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://ees.elsevier.com/imavis/
To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important that authors select “SI:Reliable Automatic” when they reach the “Article Type Name” step in the submission process.
IV. Important Dates
• 1 August 2017 – Deadline for manuscript submission
• 15 October 2017– Notification of authors
• 31 November 2017– Deadline for revised manuscripts
• 5 February 2018– Final version
For further information, please contact one of the Guest Editors listed below.
V. Guest Editors
Dr Michel Valstar
School of Computer Science,
University of Nottingham, UK
Prof Jeff Cohn
Department of Psychology/Robotics Institute
University of Pittsburgh/Carnegie Mellon University, USA
Prof Lijun Yin
Department of Computer Science
Binghamton University – State University of New York, USA