Customer's spontaneous facial expression recognition
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 observ...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2021-06-01.
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| Online Access: | Get fulltext |
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| LEADER | 02274 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs23261_15057 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Morshed, Golam |e author |
| 100 | 1 | 0 | |a Universiti Malaysia Sarawak |e contributor |
| 700 | 1 | 0 | |a Ujir, Hamimah |e author |
| 700 | 1 | 0 | |a Hipiny, Irwandi |e author |
| 245 | 0 | 0 | |a Customer's spontaneous facial expression recognition |
| 260 | |b Institute of Advanced Engineering and Science, |c 2021-06-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/23261 | ||
| 520 | |a 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. | ||
| 540 | |a Copyright (c) 2021 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Signal Processing | ||
| 690 | |a customer's emotion; face detection; facial expressions; | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 22, No 3: June 2021; 1436-1445 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v22.i3 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/23261/15057 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/23261/15057 |z Get fulltext |