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Software

pyVHR framework

Package pyVHR (short for Python framework for Virtual Heart Rate) is a comprehensive framework for studying methods of pulse rate estimation relying on video, also known as remote photoplethysmography (rPPG).

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Natural interaction

openFACS 3D framework

OpenFACS is an open source FACS-based 3D face animation system. OpenFACS is a software that allows the simulation of realistic facial expressions through the manipulation of specific action units as defined in the Facial Action Coding System.

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Affective computing

Gaze Deploy gaze model

Implementation of the gaze model "On gaze deployment to audio-visual cues of social interactions".

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Gaze processing

CLE gaze model

Constrained Levy Exploration (CLE) generates a visual scanpath by computing gaze shifts as Levy flights on any kind of saliency map (bottom-up or top-down) computed for the given image.

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Gaze processing

pyEcoSampling gaze model

Implementation of Ecological Sampling (ES) method, which generates gaze shifts on video clips (frame sequences) based on a stochastic model of eye guidance.

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Gaze processing

Gazing at social gaze model

Implementation of the gaze model "Gazing at Social Interactions Between Foraging and Decision Theory".

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Affective computing

DANTE annotation tool

DANTE (Dimensional ANnotation Tool for Emotions) is an emotional annotation tool to annotate any kind of video in terms of valence and arousal continuous dimensions.

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Affective computing

R-SVD dictionary learning algorithm

This package contains the Matlab implementation of R-SVD, an algorithm for dictionary learning in sparsity models based on the orthogonal Procrustes shape analysis.

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Sparse representations

LiMapS & k-LiMapS sparse coding algorithms

LiMapS and k-LiMapS are fast iterative methods for finding sparse solutions to underdetermined linear systems, based on a fixed-point iteration scheme which combines nonconvex Lipschitzian-type mappings with canonical orthogonal projectors.

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Sparse representations

Dataset

AMHUSE multimodal dataset

AMHUSE (A Multimodal dataset for HUmor SEnsing) is a multimodal dataset acquired with the aim to study emotional response in presence of amusement stimulus.

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Affective computing