Classification of facial expressions using SVM and HOG

Main Authors: Tanjung, Juliansyah Putra; Universitas Prima Indonesia, Muhathir, Muhathir; Universitas Medan Area
Format: Article info application/pdf Journal
Bahasa: eng
Terbitan: Universitas Medan Area , 2020
Subjects:
SVM
HOG
Online Access: http://ojs.uma.ac.id/index.php/jite/article/view/3182
http://ojs.uma.ac.id/index.php/jite/article/view/3182/2431
Daftar Isi:
  • The face is one of the human biometric which is often utilized as an important information of a person. One of the unique information of the face is facial expressions, expressions are information that is given indirectly about an expression of one's feelings. Because facial expressions have a unique pattern for each expression so that the pattern of facial expression will be tested with the computer by utilizing the Histogram of oriented gradient (HOG) descriptor as the extraction of existing features in each expression Face and information acquisition from HOG will be classified by utilizing the Support vector Mechine (SVM) method. The results of facial expression classification by utilizing the Extracaski HOG features reached 76.57% at a value of K = 500 with an average accuracy of 72.57%.