the Indian Spontaneous Expression Database (ISED)

peakImages.zip - It contains all the peak images of the included facial expression videos ISED_details.mat - It contains the details of the data included in the databas. For easy assess of the database, the paths to all the files are provided here. It also includes the position of face, nose and eyes in the peak frames of each clip. ISED_peak_images.mat - This file contains all the peak intensity images of each video clip

FACES VIDEO DATABSE

Dynamic FACES is an extension of the original FACES database . It is a database of morphed videos (n = 1,026) of young, middle-aged, and older adults displaying six naturalistic emotional facial expressions including neutrality, sadness, disgust, fear, anger, and happiness. Static images used for morphing came from the original FACES database. Videos were created by transitioning from a static neutral image to a target emotion. Videos are available in 384 x 480 pixels as .mp4 files or in origina

FACES DATABASE-HAPPINESS

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）

FACES DATABASE-SADNESS

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）

FACES database-neutrality

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）

FACES database-fear

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）

FACES database-disgust

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）

FACES database-anger

FACES is a set of images of naturalistic faces of 171 young (n = 58), middle-aged (n = 56), and older (n = 57) women and men displaying each of six facial expressions: neutrality, sadness, disgust, fear, anger, and happiness. The FACES database was developed between 2005 and 2007 by Natalie C. Ebner, Michaela Riediger, and Ulman Lindenberger at the Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.（数据库太大，分开上传）

machine learning tools for matlab

the tools contains the following algorithms: Character Recognition Using Bayesian Classifier FaceRecognitionAndReconstruction GMMClassification ImageSegmentation NeuralNetwork SVMClassification

Large Scale Facial Model (LSFM)

Large Scale Facial Model (LSFM) This repository contains the code used to produce the Large Scale Facial Model (LSFM) Large scale 3D Morphable Models ## Installing and using the LSFM 3D Morphable Model construction pipeline The code used to produce the LSFM models is **contained within this repository** The **LSFM models** were produced by using this software pipeline on the (proprietary) MeIn3D dataset.