Jindi Wang jindi.wang@durham.ac.uk
PGR Student Doctor of Philosophy
Jindi Wang jindi.wang@durham.ac.uk
PGR Student Doctor of Philosophy
Dr Ioannis Ivrissimtzis ioannis.ivrissimtzis@durham.ac.uk
Associate Professor
Zhaoxing Li
Lei Shi
Despite recent progress, hand gesture recognition, a highly regarded method of human computer interaction, still faces considerable challenges. In this paper, we address the problem of individual user style variation, which can significantly affect system performance. While previous work only supports the manual inclusion of customized hand gestures in the context of very specific application settings, here, an effective, adaptable graphical interface, supporting user-defined hand gestures is introduced. In our system, hand gestures are personalized by training a camera-based hand gesture recognition model for a particular user, using data just from that user. We employ a lightweight Multilayer Perceptron architecture based on contrastive learning, reducing the size of the data needed and the training timeframes compared to previous recognition models that require massive training datasets. Experimental results demonstrate rapid convergence and satisfactory accuracy of the recognition model, while a user study collects and analyses some initial user feedback on the system in deployment.
Wang, J., Ivrissimtzis, I., Li, Z., & Shi, L. (online). Hand gesture recognition for user-defined textual inputs and gestures. Universal Access in the Information Society, https://doi.org/10.1007/s10209-024-01139-6
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 26, 2024 |
Online Publication Date | Aug 2, 2024 |
Deposit Date | Aug 6, 2024 |
Publicly Available Date | Aug 6, 2024 |
Journal | Universal Access in the Information Society |
Print ISSN | 1615-5289 |
Electronic ISSN | 1615-5297 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
DOI | https://doi.org/10.1007/s10209-024-01139-6 |
Public URL | https://durham-repository.worktribe.com/output/2743076 |
Published Journal Article (Advance Online Version)
(2.6 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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