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Extract face landmarks using Dlib and train a multi-class SVM classifier to recognize facial expressions (emotions).

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m-elkhou/Facial_Expression_Detection

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Facial_Expression_Detection

The paper link.


Automatic Micro-Expression Recognition (AMER)

This project was about providing an Android application that can help people take charge of their own emotional health by capturing their micro expressions such as happiness, sadness, anger, disgust, surprise, fear, and neutral. This application consumes a web service which contains our finally Model. This Model predictor is created after testing different approaches for the facial expression recognition. the elaborated approaches are based on different algorithm for features extraction and different machine learning classifiers. The proposed automatic micro expression recognition (AMER) uses: OpenCV, Python and machine learning Algorithms.

Requirements

Python 3.7, and other common packages listed in requirements.txt.

App implementation

Youtube link video is shown below :


Contact & Feedback

Supervised by:

  • Mr. My Abdelouahed Sabri.

Realized by:

If you have any suggestions about papers, feel free to mail us.

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