English

Random Forest Regression for continuous affect using Facial Action Units

Computer Vision and Pattern Recognition 2022-03-30 v3 Artificial Intelligence

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.

Cite

@article{arxiv.2203.12818,
  title  = {Random Forest Regression for continuous affect using Facial Action Units},
  author = {Saurabh Hinduja and Shaun Canavan and Liza Jivnani and Sk Rahatul Jannat and V Sri Chakra Kumar},
  journal= {arXiv preprint arXiv:2203.12818},
  year   = {2022}
}
R2 v1 2026-06-24T10:24:10.668Z