Detection of confusion behavior using a facial expression based on different classification algorithms
| Autor: | Saad Mutashar Abbas, Fatima I. Yasser, Bassam H. Abd |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Facial expression
business.industry Computer science 05 social sciences 050301 education Pattern recognition 02 engineering and technology Logistic regression Support vector machine Facial Action Coding System Statistical classification Facial muscles medicine.anatomical_structure Discriminant 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Artificial intelligence medicine.symptom business 0503 education Confusion |
| Zdroj: | Engineering and Technology Journal. 39:316-325 |
| ISSN: | 2412-0758 |
| DOI: | 10.30684/etj.v39i2a.1750 |
| Popis: | Confusion detection systems (CDSs) that need Noninvasive, mobile, and cost-effective methods use facial expressions as a technique to detect confusion. In previous works, the technology that the system used represents a major gap between this proposed CDS and other systems. This CDS depends on the Facial Action Coding System (FACS) that is used to extract facial features. The FACS shows the motion of the facial muscles represented by Action Units (AUs); the movement is represented with one facial muscle or more. Seven AUs are used as possible markers for detecting confusion that has been implemented in the form of a single vector of facial action; the AUs that have been used in this work are AUs 4, 5, 6, 7, 10, 12, and 23. The database used to calculate the performance of the proposed CDS is gathered from 120 participants (91males, 29 females), between the ages of 18-45. Four types of classification algorithms are used as individuals; these classifiers are (VG-RAM), (SVM), Logistic Regression and Quadratic Discriminant classifiers. The best success rate was found when using Logistic Regression and Quadratic Discriminant. This work introduces different classification techniques to detect confusion by collecting an actual database that can be used to evaluate the performance for every CDS employing facial expressions and selecting appropriate facial features. |
| Databáze: | OpenAIRE |
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