Spatiotemporal Facial Super-Pixels for Pain Detection

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

221 Downloads (Pure)

Resumé

Pain detection using facial images is of critical importance in many eHealth applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBC- McMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios.
OriginalsprogEngelsk
TitelIX Conference on Articulated Motion and Deformable Objects
RedaktørerFrancisco José Perales, Josef Kittler
Udgivelses stedSpain
ForlagSpringer
Publikationsdato2 jul. 2016
Sider34-43
DOI
StatusUdgivet - 2 jul. 2016
BegivenhedIX Conference on Articulated Motion and Deformable Objects - Mallorca, Spanien
Varighed: 13 jul. 201615 jul. 2016
http://amdo2016.uib.es/

Konference

KonferenceIX Conference on Articulated Motion and Deformable Objects
LandSpanien
ByMallorca
Periode13/07/201615/07/2016
Internetadresse
NavnLecture Notes in Computer Science
Vol/bind9756
ISSN0302-9743

Fingerprint

Pixels

Citer dette

Lundtoft, D. H., Nasrollahi, K., Moeslund, T. B., & Guerrero, S. E. (2016). Spatiotemporal Facial Super-Pixels for Pain Detection. I F. J. Perales, & J. Kittler (red.), IX Conference on Articulated Motion and Deformable Objects (s. 34-43). Spain: Springer. Lecture Notes in Computer Science, Bind. 9756 https://doi.org/10.1007/978-3-319-41778-3_4
Lundtoft, Dennis Holm ; Nasrollahi, Kamal ; Moeslund, Thomas B. ; Guerrero, Sergio Escalera. / Spatiotemporal Facial Super-Pixels for Pain Detection. IX Conference on Articulated Motion and Deformable Objects. red. / Francisco José Perales ; Josef Kittler. Spain : Springer, 2016. s. 34-43 (Lecture Notes in Computer Science, Bind 9756).
@inproceedings{b7dae0ebb19742e2ad735652ba6d2e86,
title = "Spatiotemporal Facial Super-Pixels for Pain Detection",
abstract = "Pain detection using facial images is of critical importance in many eHealth applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBC- McMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios.",
keywords = "facial images, super-pixels, spatiotemporal filters, pain detection",
author = "Lundtoft, {Dennis Holm} and Kamal Nasrollahi and Moeslund, {Thomas B.} and Guerrero, {Sergio Escalera}",
year = "2016",
month = "7",
day = "2",
doi = "10.1007/978-3-319-41778-3_4",
language = "English",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "34--43",
editor = "Perales, {Francisco Jos{\'e}} and Josef Kittler",
booktitle = "IX Conference on Articulated Motion and Deformable Objects",
address = "Germany",

}

Lundtoft, DH, Nasrollahi, K, Moeslund, TB & Guerrero, SE 2016, Spatiotemporal Facial Super-Pixels for Pain Detection. i FJ Perales & J Kittler (red), IX Conference on Articulated Motion and Deformable Objects. Springer, Spain, Lecture Notes in Computer Science, bind 9756, s. 34-43, IX Conference on Articulated Motion and Deformable Objects, Mallorca, Spanien, 13/07/2016. https://doi.org/10.1007/978-3-319-41778-3_4

Spatiotemporal Facial Super-Pixels for Pain Detection. / Lundtoft, Dennis Holm; Nasrollahi, Kamal; Moeslund, Thomas B.; Guerrero, Sergio Escalera.

IX Conference on Articulated Motion and Deformable Objects. red. / Francisco José Perales; Josef Kittler. Spain : Springer, 2016. s. 34-43 (Lecture Notes in Computer Science, Bind 9756).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - Spatiotemporal Facial Super-Pixels for Pain Detection

AU - Lundtoft, Dennis Holm

AU - Nasrollahi, Kamal

AU - Moeslund, Thomas B.

AU - Guerrero, Sergio Escalera

PY - 2016/7/2

Y1 - 2016/7/2

N2 - Pain detection using facial images is of critical importance in many eHealth applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBC- McMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios.

AB - Pain detection using facial images is of critical importance in many eHealth applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBC- McMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios.

KW - facial images

KW - super-pixels

KW - spatiotemporal filters

KW - pain detection

U2 - 10.1007/978-3-319-41778-3_4

DO - 10.1007/978-3-319-41778-3_4

M3 - Article in proceeding

T3 - Lecture Notes in Computer Science

SP - 34

EP - 43

BT - IX Conference on Articulated Motion and Deformable Objects

A2 - Perales, Francisco José

A2 - Kittler, Josef

PB - Springer

CY - Spain

ER -

Lundtoft DH, Nasrollahi K, Moeslund TB, Guerrero SE. Spatiotemporal Facial Super-Pixels for Pain Detection. I Perales FJ, Kittler J, red., IX Conference on Articulated Motion and Deformable Objects. Spain: Springer. 2016. s. 34-43. (Lecture Notes in Computer Science, Bind 9756). https://doi.org/10.1007/978-3-319-41778-3_4