An Efficient Machine Learning Method for Facial Expression Recognition
Sachin Majithia1, Harjeet Singh2, Astha Gupta3, Neeraj Sharma4

1Mr Sachin Majithia, Assistant Professor, Chandigarh Engineering College, Landran  (Mohali), India.

2Dr. Harjeet Singh, Associate Professor, Department of Computer Science, Mata Gujri College, Fatehgarh Sahib  (Punjab), India.

3Ms. Astha Gupta, Assistant Professor in Chandigarh group of colleges, Landran  (Mohali), India.

4Mr. Neeraj Sharma, Assistant Professor, Chandigarh group of colleges, Landran  (Mohali), India.

Manuscript received on 05 August 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 26 August 2019 | PP: 549-546 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10850789S19/19©BEIESP | DOI: 10.35940/ijitee.I1085.0789S19

Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (

Abstract: Emotions play important role in human sentiments so broad studies are carried out to explore the relation between human sentiments and machine interactions. This paper deals with an automatic system which spontaneously identifies the facial emotion. Gradient filtering and component analysis is used to extract feature vector and feature optimization is taken place using swarm intelligence approach. Thus emotion recognition with optimized feature extraction process is carried out with high accuracy rate and less error probabilities. Finally the testing process is obtained for the classification of emotions and then performance is measured in terms of false acceptance rate, false rejection rate, and accuracy.

Keywords: Facial emotion Detection, Feature Extraction, Feature Optimization, Gradient Filtering.
Scope of the Article: Smart Learning Methods and Environments