TY  - CONF
AU  - Ramin Irani
AU  - Kamal Nasrollahi
AU  - Chris Bahnsen
AU  - D.H. Lundtoft
AU  - Thomas B. Moeslund
AU  - Marc O. Simon
AU  - Ciprian Corneanu
AU  - Sergio Escalera
AU  - Tanja L. Pedersen
AU  - Maria-Louise Klitgaard
AU  - Laura Petrini
A2  - CVPRW
PY  - 2015//
TI  - Spatio-temporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition
BT  - 2015 IEEE Conference on Computer Vision and Pattern Recognition  Worshops (CVPRW)
SP  - 88
EP  - 95
N2  - 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.
L1  - http://refbase.cvc.uab.es/files/INB2015.pdf
UR  - http://dx.doi.org/10.1109/CVPRW.2015.7301341
N1  - HuPBA;MILAB
ID  - Ramin Irani2015
ER  -