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Local Appearance based Novel Facial Feature Extraction Method for Human Expression Recognition

by Mohammad Shahidul Islam, Tarikuzzaman Emon, Md. Zahid Hasan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 35
Year of Publication: 2019
Authors: Mohammad Shahidul Islam, Tarikuzzaman Emon, Md. Zahid Hasan
10.5120/ijca2019918291

Mohammad Shahidul Islam, Tarikuzzaman Emon, Md. Zahid Hasan . Local Appearance based Novel Facial Feature Extraction Method for Human Expression Recognition. International Journal of Computer Applications. 181, 35 ( Jan 2019), 1-4. DOI=10.5120/ijca2019918291

@article{ 10.5120/ijca2019918291,
author = { Mohammad Shahidul Islam, Tarikuzzaman Emon, Md. Zahid Hasan },
title = { Local Appearance based Novel Facial Feature Extraction Method for Human Expression Recognition },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2019 },
volume = { 181 },
number = { 35 },
month = { Jan },
year = { 2019 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number35/30255-2019918291/ },
doi = { 10.5120/ijca2019918291 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:08:11.113875+05:30
%A Mohammad Shahidul Islam
%A Tarikuzzaman Emon
%A Md. Zahid Hasan
%T Local Appearance based Novel Facial Feature Extraction Method for Human Expression Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 35
%P 1-4
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel approach to extract the light invariant local feature for facial expression recognition is presented in this paper. It is robust in monotonic gray-scale changes caused by illumination variations. Proposed method is easy to perform and time effective. The local strength for a pixel is calculated by finding the decimal value of the neighboring of that pixel with the particular rank in term of its gray-scale value among all the nearest pixels. When eight neighboring pixels are considered, the gradient direction of the neighboring pixel with the mix of second minima and maxima of the gray scale intensity can capture more local details and yield the best performance for the facial expression recognition in our experiment. CK+ dataset is used in this experiment to find out the facial expression classification. The classification accuracy rate achieved is 92.1 ± 3.2%, which is not the best but easier to compute. The results show that the experimented feature extraction technique is fast, accurate and efficient for facial expression recognition.

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Index Terms

Computer Science
Information Sciences

Keywords

Emotion Classification Expression Recognition Image Analysis Local Descriptor Pattern Extraction.

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