Research on local visual global localization method based on out-of-view reference of spatial point association

The global localisation of spatial points is a critical step in tasks such as object tracking, motion analysis and pose measurement. This paper addresses the critical issue of global localisation when spatial points are scattered and cannot be contained within the same field of view. It proposes a local visual global localisation method based on an out-of-view reference through spatial point association. By constructing a local measurement and localisation model using parallel binocular vision and a spatial coordinate transformation model that associates local regions with the global reference, the global localisation of spatial points inside and outside the field of view is achieved. Experimental results demonstrate that the localisation accuracy of spatial points is less than 0.1 mm in terms of distance measurement. This method is useful for cooperative multi-camera localization and multi-point measurement in large 3D spaces.

Authors

Institutions

Publication Details

Journal
MATEC Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/matecconf/202541301001
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on local visual global localization method based on out-of-view reference of spatial point association

Jiale Wang, Qingping Yang, Peipei Gao, Feng Liu
MATEC Web of Conferences
Robotics and Sensor-Based Localization
article

Research on local visual global localization method based on out-of-view reference of spatial point association

Jiale Wang, Qingping Yang, Peipei Gao, Feng Liu
article en

Abstract

The global localisation of spatial points is a critical step in tasks such as object tracking, motion analysis and pose measurement. This paper addresses the critical issue of global localisation when spatial points are scattered and cannot be contained within the same field of view. It proposes a local visual global localisation method based on an out-of-view reference through spatial point association. By constructing a local measurement and localisation model using parallel binocular vision and a spatial coordinate transformation model that associates local regions with the global reference, the global localisation of spatial points inside and outside the field of view is achieved. Experimental results demonstrate that the localisation accuracy of spatial points is less than 0.1 mm in terms of distance measurement. This method is useful for cooperative multi-camera localization and multi-point measurement in large 3D spaces.

MATEC Web of ConferencesVol. 413
Tianjin University (CN), Nankai University (CN), Brunel University of London (GB)
Nankai University, Air Force Civil Engineer Center
Openalex Percentile: Top 65%
Robotics and Sensor-Based Localization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on local visual global localization method based on out-of-view reference of spatial point association — Jiale Wang, Qingping Yang, et al. · MATEC Web of Conferences (2025) | TGRS Research Map | TGRS