ExpressionNet

ExpressionNet copied to clipboard

It is a Keras implementation of a Convolutional Neural Network for Facial Expression Recognition.

Dataset

fer2013 from Kaggle Challenges

The data consists of 48x48 pixel grayscale images of faces. The faces have been automatically registered so that the face is more or less centered and occupies about the same amount of space in each image. The task is to categorize each face based on the emotion shown in the facial expression in to one of seven categories (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral). The training set consists of 28,709 examples. The public test set used for the leaderboard consists of 3,589 examples. The final test set, which was used to determine the winner of the competition, consists of another 3,589 examples.

Dependency

Keras with TensorFlow as backend

Accuracy

Finally achieve an accuracy of ~68% on the test set after 1000 epochs

Reference

https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/icmi2015_ChaZhang.pdf

https://github.com/LamUong/FacialExpressionRecognition