@InProceedings{RaminIrani2015,
author="Ramin Irani
and Kamal Nasrollahi
and Chris Bahnsen
and D.H. Lundtoft
and Thomas B. Moeslund
and Marc O. Simon
and Ciprian Corneanu
and Sergio Escalera
and Tanja L. Pedersen
and Maria-Louise Klitgaard
and Laura Petrini",
title="Spatio-temporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition",
booktitle="2015 IEEE Conference on Computer Vision and Pattern Recognition  Worshops (CVPRW)",
year="2015",
pages="88--95",
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 thermalfacial 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.",
optnote="HuPBA;MILAB",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2654), last updated on Thu, 27 Apr 2023 13:19:08 +0200",
doi="10.1109/CVPRW.2015.7301341",
file=":http://refbase.cvc.uab.es/files/INB2015.pdf:PDF"
}