Visual depression diagnosis from face based on various classification algorithms
Joint Authors
Ali, Wisam H.
Nasir, Sana A.
Hashim, Ivan A.
Source
Engineering and Technology Journal
Issue
Vol. 38, Issue 11A (30 Nov. 2020), pp.1717-1729, 13 p.
Publisher
Publication Date
2020-11-30
Country of Publication
Iraq
No. of Pages
13
Main Subjects
Topics
Abstract EN
Most psychologists believe that facial behavior through depression differs from facial behavior in the ence of depression, so facial behavior can be utilized as a dependable indicator for spotting depression.
Visual depression diagnosis system(VDD) establishesdependentson expressions of the face that are expense-effective and movable.
At this work, the VDD system is designed according to the Facial Action Coding System (FACS) to extract features of the face.
The key concept of the Facial Action Coding System (FACS) to explain the whole face behavior utilizing Action Units (AUs), every AU is linked to the motion of unique or maybe further face muscles.
Six AUs have utilized as depression features; those action units are AUs 4, 5, 6, 7, 10, and 12.
The datasets that employed to evaluate the performance of the proposed system are gathered for 125 participants (30males, 95 females); many of them are among 17-60 years of age.
At the final step of the current system, four kinds of classificationtechniques were applied separately; those classifiers algorithms are KNN, SVM, PCA, and LDA.
The outcomes of the simulation indicate that the best outcomes are achieved utilizing the KNN and LDA classifiers, where the success rate is 85% .
New classification methods in the VDD system are the key contributions of this research, gather real databases that can utilize to compute the performance of every other VDD system based on face emotions, and choose appropriate features of the face
American Psychological Association (APA)
Nasir, Sana A.& Hashim, Ivan A.& Ali, Wisam H.. 2020. Visual depression diagnosis from face based on various classification algorithms. Engineering and Technology Journal،Vol. 38, no. 11A, pp.1717-1729.
https://search.emarefa.net/detail/BIM-1236639
Modern Language Association (MLA)
Nasir, Sana A.…[et al.]. Visual depression diagnosis from face based on various classification algorithms. Engineering and Technology Journal Vol. 38, no. 11A (2020), pp.1717-1729.
https://search.emarefa.net/detail/BIM-1236639
American Medical Association (AMA)
Nasir, Sana A.& Hashim, Ivan A.& Ali, Wisam H.. Visual depression diagnosis from face based on various classification algorithms. Engineering and Technology Journal. 2020. Vol. 38, no. 11A, pp.1717-1729.
https://search.emarefa.net/detail/BIM-1236639
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1728-1729
Record ID
BIM-1236639