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 = {Zafeiriou, S and Kotsia, I and Pantic, M},
booktitle = {Face Recognition in Adverse Conditions},
doi = {10.4018/978-1-4666-5966-7.ch002},
pages = {16--37},
title = {Unconstrained face recognition},
url = {},
year = {2014}

RIS format (EndNote, RefMan)

AB - © 2014 by IGI Global. All rights reserved. The human face is the most well-researched object in computer vision, mainly because (1) it is a highly deformable object whose appearance changes dramatically under different poses, expressions, and, illuminations, etc., (2) the applications of face recognition are numerous and span several fields, (3) it is widely known that humans possess the ability to perform, extremely efficiently and accurately, facial analysis, especially identity recognition. Although a lot of research has been conducted in the past years, the problem of face recognition using images captured in uncontrolled environments including several illumination and/or pose variations still remains open. This is also attributed to the existence of outliers (such as partial occlusion, cosmetics, eyeglasses, etc.) or changes due to age. In this chapter, the authors provide an overview of the existing fully automatic face recognition technologies for uncontrolled scenarios. They present the existing databases and summarize the challenges that arise in such scenarios and conclude by presenting the opportunities that exist in the field.
AU - Zafeiriou,S
AU - Kotsia,I
AU - Pantic,M
DO - 10.4018/978-1-4666-5966-7.ch002
EP - 37
PY - 2014///
SN - 9781466659667
SP - 16
TI - Unconstrained face recognition
T1 - Face Recognition in Adverse Conditions
UR -
ER -