Evidential HMM Based Facial Expression Recognition in Medical Videos - AHOUANDJINOU, SÈMÈVO ARNAUD ROLAND MARTIAL; EZIN, C. E.; ASSOGB, KOKOU MARC; MOTAMED, Cina (My University, 2016)
A great challenge of practical significance in a recent research topic is to develop computer vision system which can automatically recognize a variety of facial expressions. Such an automated system enables to detect faces, analyzes and interprets facial expressions in a scene although the accomplishment of this task is rather strenuous. There are several related problems: detection of an image segment as a face, extraction of the facial expression information, classification of the expression (e.g., in emotion categories) and their recognition. In this paper, we proposed system that performs facial expression recognition using an Evidential Hidden Markov (Ev-HMM) model in order to manage efficiently the constraints related to facial expression recognition problem. An application of this method as part of improving the monitoring system in medical intensive care units is carried out through to analysis and interpretation of the patient face behavior. The experimental results are very exciting and have shown a promise of our automatic recognition system.
Keywords: Face Detection; Facial Expression Information Extraction; Facial Expression; Recognition; Hidden Markov Model; Transferable Belief Model Framework (TB¨M).