Energy Science, Engineering, and Policy

Emotion Estimation from Video Footage with LSTM

Abstract

Samer Attrah

Emotion estimation in general is a field that has been studied for a long time, and several approaches exist using machine learning. in this paper, we present an LSTM model, that processes the blendshapes produced by the library Media Pipe, for a face detected in a live stream of a camera, to estimate the main emotion from the facial expressions, this model is trained on the FER2013 dataset and delivers a result of 71% accuracy and 62% f1-score which meets the accuracy benchmark of the FER2013 dataset, with significantly reduced computation costs.

https://github.com/Samiratra/Emotion_estimation_from_video_footage_with_LSTM_ML_algorithm

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