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@article{1473220,
author = {Ferková, Zuzana and Urbanová, Petra and Černý, Dominik and Žuži, Marek and Matula, Petr},
article_number = {5-6},
doi = {http://dx.doi.org/10.1007/s11042-018-6869-5},
keywords = {Face reconstruction; Single photo reconstruction; Depth image database; Frontal image; Forensic anthropology},
language = {eng},
issn = {1380-7501},
journal = {Multimedia Tools and Applications},
title = {Age and gender-based human face reconstruction from single frontal image},
url = {https://link.springer.com/article/10.1007/s11042-018-6869-5},
volume = {79},
year = {2020}
}
TY - JOUR
ID - 1473220
AU - Ferková, Zuzana - Urbanová, Petra - Černý, Dominik - Žuži, Marek - Matula, Petr
PY - 2020
TI - Age and gender-based human face reconstruction from single frontal image
JF - Multimedia Tools and Applications
VL - 79
IS - 5-6
SP - 3217-3242
EP - 3217-3242
PB - Kluwer Academic Publishers
SN - 13807501
KW - Face reconstruction
KW - Single photo reconstruction
KW - Depth image database
KW - Frontal image
KW - Forensic anthropology
UR - https://link.springer.com/article/10.1007/s11042-018-6869-5
L2 - https://link.springer.com/article/10.1007/s11042-018-6869-5
N2 - We present an approach for the human face reconstruction from a single frontal image for the use in forensic anthropology when the subject’s age and gender is known. In our approach we build a database of several depth images per each age and gender group pair, marked with facial landmarks. To reconstruct a 3D facial model from an unknown frontal image we search the most similar face in the depth database based on the automatically detected landmarks and assign its depth to the model. In the evaluation part, we compared our approach to a recent automatic convolutional neural network based algorithm and a semi-automatic approach, where landmarks are required to be detected manually. In contrast to other tested approaches our algorithm can estimate all major components, such as eyes, nose and mouth, evenly. Thanks to the external depth database, it can also reconstruct human faces from images with partial facial occlusions and uneven lighting. Additionally, we have found that a single depth image provides a good approximation of the human face and a combination of multiple precomputed depth images has a little impact on the final 3D face reconstruction result. Speed measurements show that our algorithm provides a quick and a fully automatic way to reconstruct a human face from a single frontal image for the use in forensic anthropology.
ER -
FERKOVÁ, Zuzana, Petra URBANOVÁ, Dominik ČERNÝ, Marek ŽUŽI and Petr MATULA. Age and gender-based human face reconstruction from single frontal image. \textit{Multimedia Tools and Applications}. Kluwer Academic Publishers, 2020, vol.~79, 5-6, p.~3217-3242. ISSN~1380-7501. Available from: https://dx.doi.org/10.1007/s11042-018-6869-5.
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