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.
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.
Originalsprog | Engelsk |
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Titel | IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2015 |
Forlag | IEEE Computer Society Press |
Publikationsdato | 7 jun. 2015 |
Sider | 88-95 |
ISBN (Trykt) | 978-1-4673-6759-2 |
DOI | |
Status | Udgivet - 7 jun. 2015 |
Begivenhed | 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshop: Looking at People - Boston, USA Varighed: 6 jun. 2015 → 12 jun. 2015 |
Konference
Konference | 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshop |
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Land/Område | USA |
By | Boston |
Periode | 06/06/2015 → 12/06/2015 |