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Emotion-Estimation-From-Facial-Images

version 1.0.0 (11.4 MB) by Goma Najah
Emotion Estimation From Facial Images using HOG & KNN Algorithms

24 Downloads

Updated 08 Dec 2018

GitHub view license on GitHub

Prediction of emotions from facial images is one of the popular and active researches, and it’s implemented via many methods. In this thesis, the proposed system to predict emotions from facial expressions images contains several stages, first stage of this system is the pre-processing stage which is applied by detecting the face in images, then resizing the images, and then Histogram Equalization (HE) technique is applied to normalize the effects of illumination. The second stage is extracting features from facial expressions images using Histogram of Oriented Gradient (HOG), and Local Binary Pattern (LBP) feature extraction algorithms, which generates the training dataset and the testing dataset that contains expressions of Anger, Contempt, Disgust, Embarrass, Fear, Happy, Neutral, Pride, Sad, and Surprised. Then Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classifiers are used for the classification stage in order to predict the emotion. In addition, Confusion Matrix (CM) technique is used to evaluate the performance of these classifiers. The proposed system is tested on JAFFE, KDEF, MUG, WSEFEP, TFEID and ADFES databases. However, the proposed system achieved prediction rate of 96.13% when HOG+SVM method is used.

Cite As

Goma Najah (2020). Emotion-Estimation-From-Facial-Images (https://www.github.com/gomanajah/Emotion-Estimation-From-Facial-Images), GitHub. Retrieved .

Comments and Ratings (1)

qunbi Wu

please how would i solve this error?

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Emotion Estimation From Facial Images/Program/GUI (10 Expressions)

Emotion Estimation From Facial Images/Program/GUI (7 Expressions)

Emotion Estimation From Facial Images/Program/GUI (8 Expressions)