Hand Segmentation with Mask-RCNN Using Mainly Synthetic Images as Training Sets and Repetitive Training Strategy

Amin Dadgar, Guido Brunnett

2023

Abstract

We propose an approach to segment hands in real scenes. To that, we employ 1) a relatively large amount of sorely simplistic synthetic images, 2) a small number of real images, and propose 3) a training scheme of repetitive training to resolve the phenomenon we call premature learning saturation (for using relatively large training set). The results suggest the feasibility of hand segmentation subject to attending to the parameters and specifications of each category with meticulous care. We conduct a short study to quantitatively demonstrate the benefits of our repetitive training on a more general ground with the Mask-RCNN framework.

Paper Citation

in Harvard Style

Dadgar A. and Brunnett G. (2023). Hand Segmentation with Mask-RCNN Using Mainly Synthetic Images as Training Sets and Repetitive Training Strategy. 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 220-228. DOI: 10.5220/0011658900003417

in Bibtex Style

@conference{visapp23,
author={Amin Dadgar and Guido Brunnett},
title={Hand Segmentation with Mask-RCNN Using Mainly Synthetic Images as Training Sets and Repetitive Training Strategy},
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={220-228},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011658900003417},
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 - Hand Segmentation with Mask-RCNN Using Mainly Synthetic Images as Training Sets and Repetitive Training Strategy
SN - 978-989-758-634-7
AU - Dadgar A.
AU - Brunnett G.
PY - 2023
SP - 220
EP - 228
DO - 10.5220/0011658900003417
PB - SciTePress