Random Forest Regression for continuous affect using Facial Action Units

2022/03/24 by Saurabh Hinduja, Hinduja, Saurabh, Shaun Canavan +7
Psychology · #Emotion and Mood Recognition

paper · pdf · doi:10.48550/arxiv.2203.12818

Abstract

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). We extracted facial features using OpenFace and used them to train a multiple output random forest regressor. Our approach performed comparable to the baseline approach.

Related

• Facial Affective Behavior Analysis Method for 5th ABAW Competition
• Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model
• ABAW : Facial Expression Recognition in the wild
• ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges
• An Ensemble Approach for Facial Expression Analysis in Video