Learning Pain from Emotion: Transferred HoT Data Representation for Pain Intensity Estimation

Abstract. Automatic1 monitoring for the assessment of pain can sig-nificantly improve the psychological comfort of patients. Recently intro-duced databases with expert annotation opened the way for pain in-tensity estimation from facial analysis. In this contribution, pivotal face elements are identified using the Histograms of Topographical features (HoT) which are a generalization of the topographical primal sketch. In order to improve the discrimination between different pain intensity values and respectively the generalization with respect to the monitored persons, we transfer data representation from the emotion oriented Cohn-Kanade database to the UNBC McMaster Shoulder Pain database