Title: Interest emotion recognition approach using self-organising map and motion estimation

Authors: Kenza Belhouchette; Mohamed Berkane; Hacene Belhadef

Addresses: ReLaCS2 Laboratory, Larbi Ben M'Hidi University, Oum El Bouaghi, Algeria ' ReLaCS2 Laboratory, Larbi Ben M'Hidi University, Oum El Bouaghi, Algeria ' MISC Laboratory, University of Constantine 2, Algeria

Abstract: Recognising human facial emotions by computer is an interesting problem. Although several approaches have been proposed the recognition rate, amount of used resources and calculation time remain factors for improvement. Our work presents a new approach for recognising basic emotions (joy, sadness, anger, disgust, surprise and fear) in image sequences. We introduced interest emotion and created its corresponding action units (AUs) based on psychological foundations. Our approach is mainly characterised by minimising used data and consequently optimising the computing time and improving the recognition rate. The proposed approach was divided into three steps: face detection using the Viola and Jones method, the extraction of facial features: here we exploited the facial action coding system, which is based on AUs. To detect AUs, we extracted face strategic points using an active appearance model and a block-matching approach. At the last, we classified the results by using the Kohonen self-organising map (SOM).

Keywords: emotion; interest; neural network; Kohonen; action units; facial expression; bloc matching.

DOI: 10.1504/IJISTA.2019.101950

International Journal of Intelligent Systems Technologies and Applications, 2019 Vol.18 No.5, pp.494 - 508

Received: 30 Aug 2017
Accepted: 21 Feb 2018

Published online: 10 Jul 2019 *

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