Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients

Sagar Deep Deb; Manish Sharma; Chandrajit Choudhury; Fazal Ahmed Talukdar; Rabul Hussain Laskar

International Journal of Image Processing and Pattern Recognition

Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients

Abstract

An automatic facial expression classification method, based on multiscale Histogram of Oriented Gradients (HOG) features extracted from sub-facial image patches, is proposed in this paper. A number of multiclass Support Vector Machines (SVM) are designed using the multiscale HOG features for classifying six basic facial expressions for frontal face images. The proposed method, with a simple design and few training data, achieves descent classification accuracy at a very low computational complexity.Keywords: multi-scale HOG, Support Vector Machine, Sub-facial patch, histogram.Cite this Article: Sagar Deep Deb, Manish Sharma, Chandrajit Choudhury, Fazal Ahmed Talukdar, Rabul Hussain Laskar. Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients. International Journal of Image Processing and Pattern Recognition: 2020; 6(1): 5–13p.

Full text

The full text of this article is available to subscribers.

On a subscribing campus you are let in by network address, with no login at all.

One-off purchase. Permanent access to this article, no account needed.

A year of online access to every article in International Journal of Image Processing and Pattern Recognition. Or choose several journals →

How to cite

Sagar Deep Deb, Manish Sharma, Chandrajit Choudhury, Fazal Ahmed Talukdar, Rabul Hussain Laskar. Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients. International Journal of Image Processing and Pattern Recognition. 2020;6(1):5–13.

Download the citation:

Article details

Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients

Abstract

Read more of it

Publish your article

Abstract

Related articles

AI-Based Deepfake Voice Detection Model for Hindi Language

DEVELOPING A DRIVER DROWSINESS DETECTION SYSTEM (DDDS)

A Study on CNN-Based Image Mosaicing

Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model

Vani-Adapt: A Zero-Shot Accent Trans-Adaptation Framework for Robust Indic Speech Recognition

Enhancing Facial Expression Analysis Using CNNs: Insights from ML and Deep Learning Comparisons

Read more of it

Publish your article