Emotion Detection with Machine Learning
Learning deep features for image emotion classification, Ming Chen : CNN
Multimodal emotion recognition using deep learning architectures, pdf,Hiranmayi Ranganathan : CDBN
Joint Image Emotion Classification and Distribution Learning via Deep Convolutional Neural Network.,Jufeng Yang : Multitask CNN
Real-time Facial Emotion Classification Using Deep Learning, pdf, Emre Dandıl : CNN + Viola-Jones algorithm for face detection
Deep learning approaches for facial emotion recognition: A case study on FER-2013, pdf, Panagiotis Giannopoulos : AlexNet GooLeNet
A brief review of facial emotion recognition based on visual information, pdf, Byoung Chul Ko : review of FER methods, emotion classification in both spatial and temporal, there are to categories: (a) CNN, (b) CNN and LSTM, list of datesets.
A review on deep learning algorithms for speech and facial emotion recognition, pdf, Charlyn Pushpa Latha : review of (speech and facial) methods, algorithm categories: (a) DBM (b) DNN (c) CNN (c) SAE (f) others
Facial emotion recognition in real time, Dan Duncan : CNN with running average, VGGS network with a face-detector provided by OpenCV (Haar Cascade),
Facial Emotion Recognition Using Hybrid Features, pdf, Abdulrahman Alreshidi : Haar Cascade + Neighboring Difference Features (NDF)
Labeling images with facial emotion and the potential for pediatric healthcare, pdf, Haik Kalantarian : scalable aggregation of emotive frames from children with autism
Github
atulapra/Emotion-detection : haar cascade +CNN
MauryaRitesh/Facial-Expression-Detection : haar cascade + ?
kaushikjadhav01/Deep-Surveillance-Monitor-Facial-Emotion-Age-Gender-Recognition-System : haar cascade + VGGNet/Resnet
Facial-Emotion-Detection This work showcases two independent methods for recognizing emotions from faces. The first method using representational autoencoder units, a fairly original idea, to classify an image among one of the seven different emotions. The second method uses a 8-layer convolutional neural network which has an original and unique design, and was developed from scratch.
juan-csv/Face_info: face recognition, and facial attributes detection (age, gender, emotion and race)
weblineindia/AIML-Human-Attributes-Detection-with-Facial-Feature-Extraction This is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.
berksudan/Real-Time-Emotion-Detection Real time emotion detection from facial expression using both machine learning and deep learning techniques.
m-elkhou/Facial_Expression_Detection : 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. Paper
serengil/deepface : A Lightweight Deep Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Framework for Python
Ideas
Real Time Facial Feature Extraction : Emotional + others, video based, handheld based.
upgrade juan-csv/Face_info approach
Library
Jeeliz Github: open source, web app
for Drowsiness detection, by Abhilash26 aka Dinodroid: Be sure to don't fall asleep when driving thanks to this webapp! You can try it here: dont-drive-drowsy.glitch.me, view the source code or a demo video
for Expressions reader, by Abhilash26 aka Dinodroid: detects 5 high level expressions (happiness, fear, anger, surprise, sadness) from the morph coefficients given by this lib, and display them as smileys. You can try it here: emotion-reader.glitch.me or browse the source code
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