PT Unknown
AU Ramin Irani
   Kamal Nasrollahi
   Chris Bahnsen
   D.H. Lundtoft
   Thomas B. Moeslund
   Marc O. Simon
   Ciprian Corneanu
   Sergio Escalera
   Tanja L. Pedersen
   Maria-Louise Klitgaard
   Laura Petrini
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)
PY 2015
BP 88
EP 95
DI 10.1109/CVPRW.2015.7301341
AB 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.
ER