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Authors: Arnaud Lienhard ; Marion Reinhard ; Alice Caplier and Patricia Ladret

Affiliation: Grenoble University, France

ISBN: 978-989-758-004-8

Keyword(s): Aesthetic Image Quality, Portrait, Categorization, Image Segmentation.

Abstract: A single glance at a face is enough to infer a first impression about someone. With the increasing amount of pictures available, selecting the most suitable picture for a given use is a difficult task. This work focuses on the estimation of the image quality of facial portraits. Some image quality features are extracted such as blur, color representation, illumination and it is shown that concerning facial picture rating, it is better to estimate each feature on the different picture parts (background and foreground). The performance of the proposed image quality estimator is evaluated and compared with a subjective facial picture quality estimation experiment.

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Paper citation in several formats:
Lienhard, A.; Reinhard, M.; Caplier, A. and Ladret, P. (2014). Photo Rating of Facial Pictures based on Image Segmentation.In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 329-336. DOI: 10.5220/0004673003290336

@conference{visapp14,
author={Arnaud Lienhard. and Marion Reinhard. and Alice Caplier. and Patricia Ladret.},
title={Photo Rating of Facial Pictures based on Image Segmentation},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={329-336},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004673003290336},
isbn={978-989-758-004-8},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - Photo Rating of Facial Pictures based on Image Segmentation
SN - 978-989-758-004-8
AU - Lienhard, A.
AU - Reinhard, M.
AU - Caplier, A.
AU - Ladret, P.
PY - 2014
SP - 329
EP - 336
DO - 10.5220/0004673003290336

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