Pain detection through shape and appearance features. - Université Jean-Monnet-Saint-Étienne Access content directly
Conference Papers Year : 2013

Pain detection through shape and appearance features.


In this paper we are proposing a novel computer vision system that can recognize expression of pain in videos by analyzing facial features. Usually pain is reported and recorded manually and thus carry lot of subjectivity. Manual monitoring of pain makes difficult for the medical practitioners to respond quickly in critical situations. Thus, it is desirable to design such a system that can automate this task. With our proposed model pain monitoring can be done in real-time without any human intervention. We propose to extract shape information using pyramid histogram of orientation gradients (PHOG) and appearance information using pyramid local binary pattern (PLBP) in order to get discriminative representation of face. We tested our proposed model on UNBC-McMaster Shoulder Pain Expression Archive Database and recorded results that exceeds state-of-the-art.
No file

Dates and versions

ujm-00875093 , version 1 (21-10-2013)



R. A. Khan, A. Meyer, Hubert Konik, Saïda Bouakaz. Pain detection through shape and appearance features.. Multimedia and Expo (ICME), 2013 IEEE International Conference on, Jul 2013, San Jose, CA, United States. pp.1-6, ⟨10.1109/ICME.2013.6607608⟩. ⟨ujm-00875093⟩
114 View
0 Download



Gmail Facebook X LinkedIn More