Machine Vision Indoor Positioning Algorithm Based on Improved Convolutional Neural Network Structure

Wangping Zou

2025

Abstract

The role of machine vision in indoor positioning is very important, but there is a problem of inaccurate visual positioning. The manual positioning method cannot solve the machine vision problem in visual positioning, and the positioning is unreasonable. Therefore, this paper proposes an improved convolutional neural network method for machine vision indoor localization analysis. Firstly, the convolution theory is used to evaluate the indoor situation, and the indicators are divided according to the machine vision indoor positioning standards to reduce the interference factors in the indoor positioning of machine vision. Then, the convolution theory forms an indoor positioning scheme for machine vision and comprehensively analyzes the positioning results. MATLAB simulation shows that under certain conditions of the indoor environment, improving the convolutional neural network method can improve the accuracy of indoor positioning Shorten the positioning time, and the results are better than manual positioning methods.

Paper Citation

in Harvard Style

Zou W. (2025). Machine Vision Indoor Positioning Algorithm Based on Improved Convolutional Neural Network Structure. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 146-149. DOI: 10.5220/0013537000004664

in Bibtex Style

@conference{incoft25,
author={Wangping Zou},
title={Machine Vision Indoor Positioning Algorithm Based on Improved Convolutional Neural Network Structure},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={146-149},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013537000004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Machine Vision Indoor Positioning Algorithm Based on Improved Convolutional Neural Network Structure
SN - 978-989-758-763-4
AU - Zou W.
PY - 2025
SP - 146
EP - 149
DO - 10.5220/0013537000004664
PB - SciTePress