University of Hertfordshire

By the same authors

Retaining Expression on De-identified Faces

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Standard

Retaining Expression on De-identified Faces. / Meng, Li; Shenoy, Aruna.

Speech and Computer. ed. / Alexey Karpov; Rodmonga Potapova; Iosif Mporas. Springer International Publishing, 2017. p. 651-661 (Lecture Notes in Computer Science book series (LNCS, volume 10458)).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Harvard

Meng, L & Shenoy, A 2017, Retaining Expression on De-identified Faces. in A Karpov, R Potapova & I Mporas (eds), Speech and Computer. Lecture Notes in Computer Science book series (LNCS, volume 10458), Springer International Publishing, pp. 651-661, 19th International Conference, SPECOM 2017, Hatfield, United Kingdom, 12/09/17. https://doi.org/10.1007/978-3-319-66429-3

APA

Meng, L., & Shenoy, A. (2017). Retaining Expression on De-identified Faces. In A. Karpov, R. Potapova, & I. Mporas (Eds.), Speech and Computer (pp. 651-661). (Lecture Notes in Computer Science book series (LNCS, volume 10458)). Springer International Publishing. https://doi.org/10.1007/978-3-319-66429-3

Vancouver

Meng L, Shenoy A. Retaining Expression on De-identified Faces. In Karpov A, Potapova R, Mporas I, editors, Speech and Computer. Springer International Publishing. 2017. p. 651-661. (Lecture Notes in Computer Science book series (LNCS, volume 10458)). https://doi.org/10.1007/978-3-319-66429-3

Author

Meng, Li ; Shenoy, Aruna. / Retaining Expression on De-identified Faces. Speech and Computer. editor / Alexey Karpov ; Rodmonga Potapova ; Iosif Mporas. Springer International Publishing, 2017. pp. 651-661 (Lecture Notes in Computer Science book series (LNCS, volume 10458)).

Bibtex

@inbook{3acc2c8af6564d218ff5af170694a988,
title = "Retaining Expression on De-identified Faces",
abstract = "The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in the recorded documents. A face de-identification algorithm, named k-Same, has been proposed by prior research and guarantees to thwart face recognition software. However, like many previous attempts in face de-identification, kSame fails to preserve the utility such as gender and expression of the original data. To overcome this, a new algorithm is proposed here to preserve data utility as well as protect privacy. In terms of utility preservation, this new algorithm is capable of preserving not only the category of the facial expression (e.g., happy or sad) but also the intensity of the expression. This new algorithm for face de-identification possesses a great potential especially with real-world images and videos as each facial expression in real life is a continuous motion consisting of images of the same expression with various degrees of intensity.",
author = "Li Meng and Aruna Shenoy",
note = "{\circledC} Springer International Publishing AG 2017",
year = "2017",
month = "8",
day = "13",
doi = "10.1007/978-3-319-66429-3",
language = "English",
isbn = "978-3-319-66428-6",
series = "Lecture Notes in Computer Science book series (LNCS, volume 10458)",
publisher = "Springer International Publishing",
pages = "651--661",
editor = "Karpov, {Alexey } and Potapova, {Rodmonga } and Mporas, {Iosif }",
booktitle = "Speech and Computer",

}

RIS

TY - CHAP

T1 - Retaining Expression on De-identified Faces

AU - Meng, Li

AU - Shenoy, Aruna

N1 - © Springer International Publishing AG 2017

PY - 2017/8/13

Y1 - 2017/8/13

N2 - The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in the recorded documents. A face de-identification algorithm, named k-Same, has been proposed by prior research and guarantees to thwart face recognition software. However, like many previous attempts in face de-identification, kSame fails to preserve the utility such as gender and expression of the original data. To overcome this, a new algorithm is proposed here to preserve data utility as well as protect privacy. In terms of utility preservation, this new algorithm is capable of preserving not only the category of the facial expression (e.g., happy or sad) but also the intensity of the expression. This new algorithm for face de-identification possesses a great potential especially with real-world images and videos as each facial expression in real life is a continuous motion consisting of images of the same expression with various degrees of intensity.

AB - The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in the recorded documents. A face de-identification algorithm, named k-Same, has been proposed by prior research and guarantees to thwart face recognition software. However, like many previous attempts in face de-identification, kSame fails to preserve the utility such as gender and expression of the original data. To overcome this, a new algorithm is proposed here to preserve data utility as well as protect privacy. In terms of utility preservation, this new algorithm is capable of preserving not only the category of the facial expression (e.g., happy or sad) but also the intensity of the expression. This new algorithm for face de-identification possesses a great potential especially with real-world images and videos as each facial expression in real life is a continuous motion consisting of images of the same expression with various degrees of intensity.

U2 - 10.1007/978-3-319-66429-3

DO - 10.1007/978-3-319-66429-3

M3 - Chapter (peer-reviewed)

SN - 978-3-319-66428-6

T3 - Lecture Notes in Computer Science book series (LNCS, volume 10458)

SP - 651

EP - 661

BT - Speech and Computer

A2 - Karpov, Alexey

A2 - Potapova, Rodmonga

A2 - Mporas, Iosif

PB - Springer International Publishing

ER -