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An Efficient Approach to De-Identifying Faces in Videos

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An Efficient Approach to De-Identifying Faces in Videos. / Meng, Li; Sun, Zongji; Collado , Odette Tejada .

In: IET Signal Processing, Vol. 11 , No. 9, 01.12.2017, p. 1039-1045.

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Meng, Li ; Sun, Zongji ; Collado , Odette Tejada . / An Efficient Approach to De-Identifying Faces in Videos. In: IET Signal Processing. 2017 ; Vol. 11 , No. 9. pp. 1039-1045.

Bibtex

@article{8f8669961b3b4c289b2bb0992a68808a,
title = "An Efficient Approach to De-Identifying Faces in Videos",
abstract = "This study presents a novel approach that extends face de-identification from person-specific (closed) sets of facial images to open sets of video frames. Inspired by the previous work in facial expression transfer, the authors have introduced an `identity shift' to ensure identity consistency within a de-identified video sequence. The `identity shift' is derived from the first video frame of a person and is then applied in the de-identification of all subsequent frames of the same person. Experimental results show that video frames that are originally associated with the same person will remain related to a common new identity after the application of the proposed approach. In addition, the proposed approach is able to achieve privacy protection as well as preservation of dynamic facial expressions. Finally, MATLAB implementation of the approach has confirmed its potential to operate in real time at the highest standard video frame rate.",
keywords = "DATA PRIVACY, FACE RECOGNITION, IDENTIFICATION, IMAGE PROCESSING, VIDEO SIGNALS",
author = "Li Meng and Zongji Sun and Collado, {Odette Tejada}",
note = "This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/3.0/).",
year = "2017",
month = "12",
day = "1",
doi = "10.1049/iet-spr.2016.0761",
language = "English",
volume = "11",
pages = "1039--1045",
journal = "IET Signal Processing",
issn = "1751-9675",
publisher = "Institution of Engineering and Technology",
number = "9",

}

RIS

TY - JOUR

T1 - An Efficient Approach to De-Identifying Faces in Videos

AU - Meng, Li

AU - Sun, Zongji

AU - Collado , Odette Tejada

N1 - This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/3.0/).

PY - 2017/12/1

Y1 - 2017/12/1

N2 - This study presents a novel approach that extends face de-identification from person-specific (closed) sets of facial images to open sets of video frames. Inspired by the previous work in facial expression transfer, the authors have introduced an `identity shift' to ensure identity consistency within a de-identified video sequence. The `identity shift' is derived from the first video frame of a person and is then applied in the de-identification of all subsequent frames of the same person. Experimental results show that video frames that are originally associated with the same person will remain related to a common new identity after the application of the proposed approach. In addition, the proposed approach is able to achieve privacy protection as well as preservation of dynamic facial expressions. Finally, MATLAB implementation of the approach has confirmed its potential to operate in real time at the highest standard video frame rate.

AB - This study presents a novel approach that extends face de-identification from person-specific (closed) sets of facial images to open sets of video frames. Inspired by the previous work in facial expression transfer, the authors have introduced an `identity shift' to ensure identity consistency within a de-identified video sequence. The `identity shift' is derived from the first video frame of a person and is then applied in the de-identification of all subsequent frames of the same person. Experimental results show that video frames that are originally associated with the same person will remain related to a common new identity after the application of the proposed approach. In addition, the proposed approach is able to achieve privacy protection as well as preservation of dynamic facial expressions. Finally, MATLAB implementation of the approach has confirmed its potential to operate in real time at the highest standard video frame rate.

KW - DATA PRIVACY, FACE RECOGNITION, IDENTIFICATION, IMAGE PROCESSING, VIDEO SIGNALS

U2 - 10.1049/iet-spr.2016.0761

DO - 10.1049/iet-spr.2016.0761

M3 - Article

VL - 11

SP - 1039

EP - 1045

JO - IET Signal Processing

JF - IET Signal Processing

SN - 1751-9675

IS - 9

ER -