Spatiotemporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition

Ramin Irani, Kamal Nasrollahi, Marc Oliu Simon, Ciprian Corneanu, Sergio Escalera Guerrero, Chris Bahnsen, Dennis Holm Lundtoft, Thomas B. Moeslund, Tanja Pedersen, Marie-Louise Klitgaard, Laura Petrini

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29 Citationer (Scopus)
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Abstract

Pain is a vital sign of human health and its automatic detection
can be of crucial importance in many different contexts,
including medical scenarios. While most available
computer vision techniques are based on RGB, in this paper,
we investigate the effect of combining RGB, depth, and thermal
facial images for pain detection and pain intensity level
recognition. For this purpose, we extract energies released
by facial pixels using a spatiotemporal filter. Experiments
on a group of 12 elderly people applying the multimodal approach
show that the proposed method successfully detects
pain and recognizes between three intensity levels in 82%
of the analyzed frames improving more than 6% over RGB
only analysis in similar conditions.
OriginalsprogEngelsk
TitelIEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2015
ForlagIEEE Computer Society Press
Publikationsdato7 jun. 2015
Sider88-95
ISBN (Trykt)978-1-4673-6759-2
DOI
StatusUdgivet - 7 jun. 2015
Begivenhed2015 IEEE Conference on Computer Vision and Pattern Recognition Workshop: Looking at People - Boston, USA
Varighed: 6 jun. 201512 jun. 2015

Konference

Konference2015 IEEE Conference on Computer Vision and Pattern Recognition Workshop
Land/OmrådeUSA
ByBoston
Periode06/06/201512/06/2015

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