Open AccessImpact of eye detection error on face recognition performance
Author(s) -
Dutta Abhishek,
Günther Manuel,
El Shafey Laurent,
Marcel Sébastien,
Veldhuis Raymond,
Spreeuwers Luuk
Publication year - 2015
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
ISSN - 2047-4946
DOI - 10.1049/iet-bmt.2014.0037
Subject(s) - computer science , facial recognition system , preprocessor , artificial intelligence , face (sociological concept) , face detection , computer vision , pattern recognition (psychology) , ambiguity , detector , speech recognition , social science , sociology , programming language , telecommunications
The locations of the eyes are the most commonly used features to perform face normalisation (i.e. alignment of facial features), which is an essential preprocessing stage of many face recognition systems. In this study, the authors study the sensitivity of open source implementations of five face recognition algorithms to misalignment caused by eye localisation errors. They investigate the ambiguity in the location of the eyes by comparing the difference between two independent manual eye annotations. They also study the error characteristics of automatic eye detectors present in two commercial face recognition systems. Furthermore, they explore the impact of using different eye detectors for training/enrolment and query phases of a face recognition system. These experiments provide an insight into the influence of eye localisation errors on the performance of face recognition systems and recommend a strategy for the design of training and test sets of a face recognition algorithm.