Customer’s Spontaneous Facial Expression Recognition

Golam, Morshed and Hamimah, Ujir and Irwandi, Hipiny (2021) Customer’s Spontaneous Facial Expression Recognition. Indonesian Journal of Electrical Engineering and Computer Science, 22 (3). pp. 1436-1445. ISSN 2502-4752

[img] PDF
23261-48306-1-PB.pdf

Download (747kB)
Official URL: http://ijeecs.iaescore.com/index.php/IJEECS/index

Abstract

In the field of consumer science, customer facial expression is often categorized either as negative or positive. Customer who portrays negative emotion to a specific product mostly means they reject the product while a customer with positive emotion is more likely to purchase the product. To observe customer emotion, many researchers have studied different perspectives and methodologies to obtain high accuracy results. Conventional neural network (CNN) is used to recognize customer spontaneous facial expressions. This paper aims to recognize customer spontaneous expressions while the customer observed certain products. We have developed a customer service system using a CNN that is trained to detect three types of facial expression, i.e. happy, sad, and neutral. Facial features are extracted together with its histogram of gradient and sliding window. The results are then compared with the existing works and it shows an achievement of 82.9% success rate on average.

Item Type: Article
Uncontrolled Keywords: Customer’s emotion Face detection, UNIMAS, Univeristy, Borneo, Malaysia,Sarawak, Kuching, Samarahan, IPTA, education, Universiti Malaysia Sarawak Facial expressions,
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Ujir
Date Deposited: 21 Jun 2021 10:08
Last Modified: 21 Jun 2021 10:08
URI: http://ir.unimas.my/id/eprint/35506

Actions (For repository members only: login required)

View Item View Item