Point Distribution Models for Pose Robust Face Recognition: Advantages of Correcting Pose Parameters Over Warping Faces to Mean Shape

Daniel González-Jiménez, José Luis Alba-Castro

Abstract

In the context of pose robust face recognition, some approaches in the literature aim to correct the original faces by synthesizing virtual images facing a standard pose (e.g. a frontal view), which are then fed into the recognition system. One way to do this is by warping the incoming face onto the average frontal shape of a training dataset, bearing in mind that discriminative information for classification may have been thrown away during the warping process, especially if the incoming face shape differs enough from the average shape. Recently, it has been proposed a method for generating synthetic frontal images by modification of a subset of parameters from a Point Distribution Model (the so-called pose parameters), and texture mapping. We demonstrate that if only pose parameters are modified, client specific information remains in the warped image and discrimination between subjects is more reliable. Statistical analysis of the verification experiments conducted on the XM2VTS database confirms the benefits of modifying only the pose parameters over warping onto a mean shape.

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Paper Citation


in Harvard Style

González-Jiménez D. and Luis Alba-Castro J. (2007). Point Distribution Models for Pose Robust Face Recognition: Advantages of Correcting Pose Parameters Over Warping Faces to Mean Shape . In Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007) ISBN 978-972-8865-93-1, pages 138-147. DOI: 10.5220/0002428001380147


in Bibtex Style

@conference{pris07,
author={Daniel González-Jiménez and José Luis Alba-Castro},
title={Point Distribution Models for Pose Robust Face Recognition: Advantages of Correcting Pose Parameters Over Warping Faces to Mean Shape},
booktitle={Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007)},
year={2007},
pages={138-147},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002428001380147},
isbn={978-972-8865-93-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2007)
TI - Point Distribution Models for Pose Robust Face Recognition: Advantages of Correcting Pose Parameters Over Warping Faces to Mean Shape
SN - 978-972-8865-93-1
AU - González-Jiménez D.
AU - Luis Alba-Castro J.
PY - 2007
SP - 138
EP - 147
DO - 10.5220/0002428001380147