m-elkhou/Facial_Expression_Detection
Extract face landmarks using Dlib and train a multi-class SVM classifier to recognize facial expressions (emotions).
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.
- AndroidApplication : The APK file of the Android application.
- ProjectCode : The python code of the whole project.
- FlaskServerCode : The code of the Flask server.
- AndroidAppSourceCode : The source code of the Android App.
- Presentation : Contains A power Point file which presents our work.
- ic_launcher-web : Logo of the Android Application.
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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