Imperial College London


Faculty of EngineeringDepartment of Computing

Professor in Machine Learning & Computer Vision



+44 (0)20 7594 8461s.zafeiriou Website CV




375Huxley BuildingSouth Kensington Campus






BibTex format

author = {Valstar, MF and Zafeiriou, S and Pantic, M},
booktitle = {Face Recognition in Adverse Conditions},
doi = {10.4018/978-1-4666-5966-7.ch008},
pages = {167--186},
title = {Facial action recognition in 2D and 3D},
url = {},
year = {2014}

RIS format (EndNote, RefMan)

AB - © 2014 by IGI Global. All rights reserved. Automatic Facial Expression Analysis systems have come a long way since the earliest approaches in the early 1970s. We are now at a point where the first systems are commercially applied, most notably smile detectors included in digital cameras. As one of the most comprehensive and objective ways to describe facial expressions, the Facial Action Coding System (FACS) has received significant and sustained attention within the field. Over the past 30 years, psychologists and neuroscientists have conducted extensive research on various aspects of human behaviour using facial expression analysis coded in terms of FACS. Automating FACS coding would make this research faster and more widely applicable, opening up new avenues to understanding how we communicate through facial expressions. Mainly due to the cost effectiveness of existing recording equipment, until recently almost all work conducted in this area involves 2D imagery, despite their inherent problems relating to pose and illumination variations. In order to deal with these problems, 3D recordings are increasingly used in expression analysis research. In this chapter, the authors give an overview of 2D and 3D FACS recognition, and summarise current challenges and opportunities.
AU - Valstar,MF
AU - Zafeiriou,S
AU - Pantic,M
DO - 10.4018/978-1-4666-5966-7.ch008
EP - 186
PY - 2014///
SN - 9781466659667
SP - 167
TI - Facial action recognition in 2D and 3D
T1 - Face Recognition in Adverse Conditions
UR -
ER -