PAINFUL DATA:

The UNBC-McMaster Shoulder Pain Expression Archive

Patrick Lucey, Jeffrey F. Cohn, Kenneth Prkachin, Patricia Solomon & Iain Matthews

Carnegie Mellon University, University of Pittsburgh, University of Northern British Columbia,

McMaster University, and Disney Research Pittsburgh

To obtain the archive for research use, please see Downloads.  

To learn about the Pain Archive and recent findings:

Ashraf, A. B., Lucey, S., Cohn, J. F., Chen, T., Prkachin, K., & Solomon, P. (2009). The painful face: Pain expression recognition using active appearance models. Image and Vision Computing, 27, 1788-1796.  IVCJ2009.pdf

Lucey, P., Cohn, J.F., Prkachin, K.M., Solomon, P., & Matthews, I. (2011). Painful data: The UNBC-McMaster Shoulder Pain Expression Archive Database. IEEE International Conference on Automatic Face and Gesture Recognition (FG2011). PAFG2011

Lucey, P., Cohn, J. F., Howlett, J., Lucey, S., & Sridharan, S. (In press). Recognizing emotion with head pose variation: Identifying pain segments in video. Systems, Man, and Cybernetics - Part B. http://www.cs.cmu.edu/~jeffcohn/pubs/IEEE_SMC_Pain_2010_final.pdf

Prkachin, K.M. & Solomon, P.E. (2008). The structure, reliability and validity of pain expression: Evidence from patients with shoulder pain. Pain, 139, 267-274. P&S2008.pdf