Publication detail

Facial image de-identification using active appearance model

KŘÍŽ, P. PŘINOSIL, J. ŘÍHA, K. DUTTA, M. ISSAC, A.

Original Title

Facial image de-identification using active appearance model

Type

conference paper

Language

English

Original Abstract

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.

Keywords

Image reconstruction, Biometrics (access control), Databases, Active appearance model, Robustness, Computational modeling

Authors

KŘÍŽ, P.; PŘINOSIL, J.; ŘÍHA, K.; DUTTA, M.; ISSAC, A.

Released

17. 11. 2017

Publisher

IEEE

Location

Dehradun, India

ISBN

978-1-5386-1147-0

Book

2017 International Conference on Emerging Trends in Computing and Communication Technologies

Pages from

1

Pages to

5

Pages count

5

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/"
}