Publication: Child Head Gesture Classification through Transformers
Type:
Article
Date
2022-11-04
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
This paper proposes a transformer network for head pose classification (HPC) which outperforms the existing SoA for HPC. This robust model is then extended to overcome the limited child data challenge by applying transfer learning resulting in an accuracy of 95.34% for child HPC in the wild.
Description
Keywords
Head Pose Estimation, Logistic Regression, SVM, Transfer Learning, Transformer
Citation
N. Wedasingha, P. Samarasinghe, D. Singarathnam, M. Papandrea, A. Puiatti and L. Seneviratne, "Child Head Gesture Classification through Transformers," TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON), Hong Kong, Hong Kong, 2022, pp. 1-6, doi: 10.1109/TENCON55691.2022.9977990.
