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

Publication: Research - peer-reviewArticle in proceeding

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.
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Details

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.
Original languageEnglish
Title of host publicationIEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2015
PublisherIEEE Computer Society Press
Publication date7 Jun 2015
Pages88-95
ISBN (print)978-1-4673-6759-2
DOI
StatePublished - 7 Jun 2015
Event2015 IEEE Conference on Computer Vision and Pattern Recognition Workshop - Boston, United States

Conference

Conference2015 IEEE Conference on Computer Vision and Pattern Recognition Workshop
LandUnited States
ByBoston
Periode06/06/201512/06/2015

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