Co-Incrementation: Combining Co-Training and Incremental Learning for Subject-Specific Facial Expression Recognition

Jordan Gonzalez, Thibault Geoffroy, Aurelia Deshayes, Lionel Prevost

2023

Abstract

In this work, we propose to adapt a generic emotion recognizer to a set of individuals in order to improve its accuracy. As this adaptation is weakly supervised, we propose a hybrid framework, the so-called co-incremental learning that combines semi-supervised co-training and incremental learning. The classifier we use is a specific random forest whose internal nodes are nearest class mean classifiers. It has the ability to learn incrementally data covariate shift. We use it in a co-training process by combining multiple view of the data to handle unlabeled data and iteratively learn the model. We performed several personalization and provided a comparative study between these models and their influence on the co-incrementation process. Finally, an in-depth study of the behavior of the models before, during and after the co-incrementation process was carried out. The results, presented on a benchmark dataset, show this hybrid process increases the robustness of the model, with only a few labeled data.

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Paper Citation


in Harvard Style

Gonzalez J., Geoffroy T., Deshayes A. and Prevost L. (2023). Co-Incrementation: Combining Co-Training and Incremental Learning for Subject-Specific Facial Expression Recognition. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 270-280. DOI: 10.5220/0011635200003411


in Bibtex Style

@conference{icpram23,
author={Jordan Gonzalez and Thibault Geoffroy and Aurelia Deshayes and Lionel Prevost},
title={Co-Incrementation: Combining Co-Training and Incremental Learning for Subject-Specific Facial Expression Recognition},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={270-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011635200003411},
isbn={978-989-758-626-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Co-Incrementation: Combining Co-Training and Incremental Learning for Subject-Specific Facial Expression Recognition
SN - 978-989-758-626-2
AU - Gonzalez J.
AU - Geoffroy T.
AU - Deshayes A.
AU - Prevost L.
PY - 2023
SP - 270
EP - 280
DO - 10.5220/0011635200003411