A Wearable Device Application for Human-Object Interactions Detection

Michele Mazzamuto, Francesco Ragusa, Alessandro Resta, Giovanni Farinella, Antonino Furnari

2023

Abstract

Over the past ten years, wearable technologies have continued to evolve. In the development of wearable technology, smart glasses for augmented and mixed reality are becoming particularly prominent. We believe that it is crucial to incorporate artificial intelligence algorithms that can understand real-world human behavior into these devices if we want them to be able to properly mix the real and virtual worlds and give assistance to the users. In this paper, we present an application for smart glasses that provides assistance to workers in an industrial site recognizing human-object interactions. We propose a system that utilizes a 2D object detector to locate and identify the objects in the scene and classic mixed reality features like plane detector, virtual object anchoring, and hand pose estimation to predict the interaction between a person and the objects placed on a working area in order to avoid the 3D object annotation and detection problem. We have also performed a user study with 25 volunteers who have been asked to complete a questionnaire after using the application to assess the usability and functionality of the developed application.

Paper Citation

in Harvard Style

Mazzamuto M., Ragusa F., Resta A., Farinella G. and Furnari A. (2023). A Wearable Device Application for Human-Object Interactions Detection. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 664-671. DOI: 10.5220/0011725800003417

in Bibtex Style

@conference{visapp23,
author={Michele Mazzamuto and Francesco Ragusa and Alessandro Resta and Giovanni Farinella and Antonino Furnari},
title={A Wearable Device Application for Human-Object Interactions Detection},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={664-671},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011725800003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - A Wearable Device Application for Human-Object Interactions Detection
SN - 978-989-758-634-7
AU - Mazzamuto M.
AU - Ragusa F.
AU - Resta A.
AU - Farinella G.
AU - Furnari A.
PY - 2023
SP - 664
EP - 671
DO - 10.5220/0011725800003417
PB - SciTePress