Pain detection through shape and appearance features.

R. A. Khan; A. Meyer; Hubert Konik; Saïda Bouakaz

Pain detection through shape and appearance features.

R. A. Khan ¹ A. Meyer ¹ Hubert Konik ² Saïda Bouakaz ¹

1 SAARA - Simulation, Analyse et Animation pour la Réalité Augmentée

LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information

2 LHC - Laboratoire Hubert Curien [Saint Etienne]

Abstract : 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.

Document type :

Conference papers

Domain :

Engineering Sciences [physics] / Signal and Image processing

Computer Science [cs] / Signal and Image Processing

Complete list of metadatas

https://hal-ujm.archives-ouvertes.fr/ujm-00875093
Contributor : Hubert Konik <>
Submitted on : Monday, October 21, 2013 - 10:05:29 AM
Last modification on : Thursday, November 1, 2018 - 1:19:22 AM

Pain detection through shape and appearance features.

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Pain detection through shape and appearance features.

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