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Detail publikace
KŘÍŽ, P. PŘINOSIL, J. ŘÍHA, K. DUTTA, M. ISSAC, A.
Originální název
Facial image de-identification using active appearance model
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Nowadays, the task of preservation of personal data present in public audio-visual records becomes more important. This paper describes an image processing method for de-identification of visual personal data based on a facial image. There are many primitive methods with high robustness but image quality of de-identified data is usually very poor. The advantages of this proposed method include especially very good results in quality preservation of the original image data and the possibility of a partial image reconstruction from de-identified data. The main objective has been achieved by using Active Appearance Model algorithm tested on a created database with the overall success rate of automatic recognition tool around 0.8 %. The de-identified image data look also authentic and it is possible to determine the expression or gender of the de-identified person.
Klíčová slova
Image reconstruction, Biometrics (access control), Databases, Active appearance model, Robustness, Computational modeling
Autoři
KŘÍŽ, P.; PŘINOSIL, J.; ŘÍHA, K.; DUTTA, M.; ISSAC, A.
Vydáno
17. 11. 2017
Nakladatel
IEEE
Místo
Dehradun, India
ISBN
978-1-5386-1147-0
Kniha
2017 International Conference on Emerging Trends in Computing and Communication Technologies
Strany od
1
Strany do
5
Strany počet
URL
https://ieeexplore.ieee.org/document/8280304/
BibTex
@inproceedings{BUT147372, author="Petr {Kříž} and Jiří {Přinosil} and Kamil {Říha} and Malay Kishore {Dutta} and Ashish {Issac}", title="Facial image de-identification using active appearance model", booktitle="2017 International Conference on Emerging Trends in Computing and Communication Technologies", year="2017", pages="1--5", publisher="IEEE", address="Dehradun, India", doi="10.1109/ICETCCT.2017.8280304", isbn="978-1-5386-1147-0", url="https://ieeexplore.ieee.org/document/8280304/" }