NatenaelTBekele / Facial-Expression-Emotion-Recognition-Model

The aim of this project is to classify people’s emotions based on their face images

Emotion-AI

• Artificial Emotional Intelligence or Emotion AI is a branch of AI that allow computers to understand human non-verbal cues such as body language and facial expressions.
• Affectiva offers cutting edge emotion AI tech: https://www.affectiva.com/
• The data has more than 20000 facial images, with their associated facial expression labels and around 2000 images with their facial key-point annotations.

Source: https://www.kaggle.com/c/facial-keypoints-detection/overview

Source: https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data

PART 1. FACIAL KEY POINTS DETECTION

• create a deep learning model based on Convolutional Neural Network and Residual Blocks to predict facial key-points.
• The dataset consists of x and y coordinates of 15 facial key points.
• Input Images are 96 x 96 pixels.
• Images consist of only one color channel (gray-scale images).

PART 2. FACIAL EXPRESSION DETECTION

The second model will classify people’s emotion. Data contains images that belong to 5 categories: 0 = Angry 1 = Disgust 2 = Sad 3 = Happy 4 = Surprise

PART 3. COMBINE BOTH FACIAL EXPRESSION AND KEY POINTS DETECTION MODELS