Facial Expression Recognition

Built With

• Python
• Jupyter NoteBook
• Google Colab

Problem

• Given a set of facial images (48x48 pixel grayscale images of faces (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral)

Way to go

• Face Detection - Location of face in the scene (image or video)
• Extracting information about facial features from the detected faces.
• Facial Expression and Emotion Classification - Classifying the obtained information into expression interpretative categories such as smile or frown or emotion categories such as happy, anger, disgust etc.

Approach

Data Preprocessing

• Read image, resize it again to 48x48 pixel dimention and convert it to grayscale

Data Augmentation

• I used variety of data augmentation that is implemented in Keras such as : flip, zoom, rotation to increase model performance

Algorithms

• Neutral Network approach with 7 Convolution Layer and 1 Fully Connected layer

Result

Model Loss

Model Accuracy