This is a project for detecting/classifying human facial expressions. The larger context is towards the abilities for AI agents (or robots more specifically) to interact with human agents. Human agents communicate in varying levels, from verbal to non-verbal forms. Facial expressions are a non-verbal form.
Ultimately, it is about the possibility of an AI to attain something akin to theory of mind: the ability to recognize an other as a conscious agent with intentions and feelings as well as external behaviors, which motivate those behaviors.
https://karenfisher-88874.medium.com/can-ai-read-emotional-expression-1a64cac15084
LiveDetect.py -- Python script to demonstrate the use of a predictive model in real-time inference.
Notebooks -- contains Jupyter notebooks exploring a variety of machine learning approaches, including face landmark detection for expression embedding, random forest and SVM classifiers, as well as convolutional neural networks. Run predominantly in Google Colab.
Models -- Trained convolutional models
Data -- the original FER2013 dataset, as downloaded from Kaggle, in ZIP form.
Images -- imgaes to be used in publications
References -- Bibliographical material for research and reference
Dependencies are OpenCV, TensorFlow. Python version 3.6