Facial Expression Recognition Using Proposed Geometric Features

EasyChair Preprint 4864, version 1

Abstract

Facial expression recognition has significant benefit due to its possible applications in computer vision. In this paper, new geometric based features are proposed for the recognition of seven facial expressions. The number of features is reduced by using feature selection methods. Obtained features are applied to SVM classifier. In the experimental studies, the extended Cohn-Kanade (CK+) dataset is used. Satisfactory results are obtained for the features selected with sequential backward method

Keyphrases: Support Vector Machine, facial expression recognition, feature selection, geometric based features

@booklet{EasyChair:4864,
  author    = {Nuri Özbey and Mehmet Bilginer Gülmezoğlu},
  title     = {Facial Expression Recognition Using Proposed Geometric Features},
  howpublished = {EasyChair Preprint 4864},
  year      = {EasyChair, 2021}}