Facial Expression Recognition Using Facial Landmarks and Random Forest Classifier

Human emotions are the universally common mode of interaction. Automated human facial expression identification has its own advantages. In this paper, the author has proposed and developed a methodology to identify facial emotions using facial landmarks and random forest classifier. Firstly, faces a...

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Bibliographic Details
Published in2018 IEEE ACIS 17th International Conference on Computer and Information Science (ICIS) pp. 423 - 427
Main Author Munasinghe, M. I. N. P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2018
Subjects
Eyebrows
Face recognition
Facial Expression Recognition
Facial Landmarks
Feature extraction
Forestry
Random Forests
Support vector machines
Training
Online AccessGet full text
DOI10.1109/ICIS.2018.8466510

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Summary:Human emotions are the universally common mode of interaction. Automated human facial expression identification has its own advantages. In this paper, the author has proposed and developed a methodology to identify facial emotions using facial landmarks and random forest classifier. Firstly, faces are identified in each image using a histogram of oriented gradients with a linear classifier, image pyramid, and sliding window detection scheme. Then facial landmarks are identified using a model trained with the iBUG 300-W dataset. A feature vector is calculated using a proposed method which uses identified facial landmarks and it is normalized using a proposed method in order to remove facial size variations. The same feature vector is calculated for the neutral pose and vector difference is used to identify emotions using random forest classifier. Famous Extended Cohn-Kanade database has been used to train random forest and to test the accuracy of the system.
DOI:10.1109/ICIS.2018.8466510