Automatic Facial Expression Detection Using Genetic Algorithm with SVM

  • Ekta Singh, Rajnesh Singh
Keywords: Recognition of the emotion, face, action, and facial recognition are all terms that have been used to describe computer vision.

Abstract

The discovery of photo designs within a set of photos is known as face mining. Vision, image management, knowledge mining, artificial intelligence, AI, database, and reasoning for people are all used in this operation, including information computers (PC) (personal computer). Facial recognition deconstructs and takes account of examples from facial photographs. Extracting facial features is identifying by a computer programme of highlights on human faces, such as brows ,lip and also eye. Here analysis of PCA results, GMM,GLCM and SVM (Support Vector Machines), in which the outward appearances of seven different persons are found in a database, including rage, sadness, happiness, disgust, neutrality, fear and surprise. The following are described in this paper: The purpose of this debate is to address the most successful facial recognition systems. The current research demonstrates the feasibility of awareness of physical appearance monitoring and human-computer communication.

Published
2021-10-27
How to Cite
Rajnesh Singh, E. S. (2021). Automatic Facial Expression Detection Using Genetic Algorithm with SVM. Design Engineering, 7488-7506. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/5790
Section
Articles