Detailed Information on Publication Record
2020
Age and gender-based human face reconstruction from single frontal image
FERKOVÁ, Zuzana, Petra URBANOVÁ, Dominik ČERNÝ, Marek ŽUŽI, Petr MATULA et. al.Basic information
Original name
Age and gender-based human face reconstruction from single frontal image
Authors
FERKOVÁ, Zuzana (703 Slovakia, guarantor, belonging to the institution), Petra URBANOVÁ (203 Czech Republic, belonging to the institution), Dominik ČERNÝ (203 Czech Republic, belonging to the institution), Marek ŽUŽI (703 Slovakia, belonging to the institution) and Petr MATULA (203 Czech Republic, belonging to the institution)
Edition
Multimedia Tools and Applications, Kluwer Academic Publishers, 2020, 1380-7501
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10200 1.2 Computer and information sciences
Country of publisher
Netherlands
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 2.757
RIV identification code
RIV/00216224:14330/20:00115015
Organization unit
Faculty of Informatics
UT WoS
000519410700009
Keywords in English
Face reconstruction; Single photo reconstruction; Depth image database; Frontal image; Forensic anthropology
Tags
Tags
International impact, Reviewed
Změněno: 2/2/2021 16:02, doc. RNDr. Petra Urbanová, Ph.D.
Abstract
V originále
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.
Links
MUNI/A/0854/2017, interní kód MU |
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MUNI/A/1018/2018, interní kód MU |
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MUNI/A/1153/2019, interní kód MU |
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MUNI/A/1400/2018, interní kód MU |
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