Low-power Machine Learning for Visitor Engagement in Museums

Marcus Winter, Lauren Sweeney, Katie Mason, Phil Blume

2022

Abstract

Low-power Machine Learning (ML) technologies that process data locally on consumer-level hardware are well suited for interactive applications, however, their potential for audience engagement in museums is largely unexplored. This paper presents a case study using lightweight ML models for human pose estimation and gesture classification to enable visitors’ engagement with interactive projections of interior designs. An empirical evaluation found the application is highly engaging and motivates visitors to learn more about the designs. Uncertainty in ML predictions, experienced as tracking inaccuracies, jitter, or gesture recognition problems, have little impact on their positive user experience. The findings warrant future research to explore the potential of low-power ML for visitor engagement in other use cases and heritage contexts.

Paper Citation

in Harvard Style

Winter M., Sweeney L., Mason K. and Blume P. (2022). Low-power Machine Learning for Visitor Engagement in Museums. In Proceedings of the 6th International Conference on Computer-Human Interaction Research and Applications - Volume 1: CHIRA, ISBN 978-989-758-609-5, pages 236-243. DOI: 10.5220/0011585600003323

in Bibtex Style

@conference{chira22,
author={Marcus Winter and Lauren Sweeney and Katie Mason and Phil Blume},
title={Low-power Machine Learning for Visitor Engagement in Museums},
booktitle={Proceedings of the 6th International Conference on Computer-Human Interaction Research and Applications - Volume 1: CHIRA,},
year={2022},
pages={236-243},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011585600003323},
isbn={978-989-758-609-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Computer-Human Interaction Research and Applications - Volume 1: CHIRA,
TI - Low-power Machine Learning for Visitor Engagement in Museums
SN - 978-989-758-609-5
AU - Winter M.
AU - Sweeney L.
AU - Mason K.
AU - Blume P.
PY - 2022
SP - 236
EP - 243
DO - 10.5220/0011585600003323