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Found 11 papers, 0 papers with code
Random Forest Regression for continuous affect using Facial Action Units
In this paper we describe our approach to the arousal and valence track of the 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW).
Quantified Facial Expressiveness for Affective Behavior Analytics
The quantified measurement of facial expressiveness is crucial to analyze human affective behavior at scale.
Accounting for Affect in Pain Level Recognition
In this work, we address the importance of affect in automated pain assessment and the implications in real-world settings.
Quantified Facial Temporal-Expressiveness Dynamics for Affect Analysis
The quantification of visual affect data (e. g. face images) is essential to build and monitor automated affect modeling systems efficiently.
Impact of Action Unit Occurrence Patterns on Detection
In this paper we investigate the impact of action unit occurrence patterns on detection of action units.
Impact of multiple modalities on emotion recognition: investigation into 3d facial landmarks, action units, and physiological data
Considering this, we present an analysis of 3D facial data, action units, and physiological data as it relates to their impact on emotion recognition.
Facial Action Unit Detection using 3D Facial Landmarks
In this paper, we propose to detect facial action units (AU) using 3D facial landmarks.
Detecting Forged Facial Videos using convolutional neural network
In this paper, we propose to detect forged videos, of faces, in online videos.
Subject Identification Across Large Expression Variations Using 3D Facial Landmarks
Landmark localization is an important first step towards geometric based vision research including subject identification.
Studying the Impact of Mood on Identifying Smartphone Users
This paper explores the identification of smartphone users when certain samples collected while the subject felt happy, upset or stressed were absent or present.
Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis
The corpus further includes derived features from 3D, 2D, and IR (infrared) sensors and baseline results for facial expression and action unit detection.
