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 ob...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Institute of Advanced Engineering and Science: IAES
2021
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/35508/1/210621.pdf http://ir.unimas.my/id/eprint/35508/ http://ijeecs.iaescore.com/index.php/IJEECS |
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| Summary: | 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. |
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