Video map: A realtime orthographic geo-image considering DEM and semantic information

Aiming at the problem that it is difficult to accurately calibrate massive Pan-Tilt-Zoom Camera (PTZ) cameras on telecommunication tower and the visualization effect of orthographic geo-image is poor, this paper proposes a new method of realtime orthographic geo-image generating, which is considering Digital Elevation Model (DEM) and semantic information (ROGI-DS). First, through integrating tower cameras with 3D GIS, a camera calibration method based on view fitting (3D GIS-GeoC) is designed. Then, using the trained semantic segmentation model (TCSM), the sky area can automatically be identified and removed. Finally, based on the results of camera calibration and viewshed analysis, and the orthographic geo-image are generated. The results show that: (1) 3D GIS-GeoC method outperforms the traditional Perspective-n-Point (PnP) algorithm;(2) The tower camera semantic segmentation model (TCSM) achieves an accuracy of 96.7%; (3) ROGI-DS method improves the accuracy and visualization of orthographic geo-image under different terrain constraints, and can be used real-time monitoring of natural resources and emergency reliefs.

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Publication Details

Journal
PLoS ONE
Published
2025-05-14
DOI
https://doi.org/10.1371/journal.pone.0323669
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00

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article

Video map: A realtime orthographic geo-image considering DEM and semantic information

Xingguo Zhang, Shuai Ren, Sen Yang, Mohan Liu et al.
PLoS ONE
Robotics and Sensor-Based Localization
article

Video map: A realtime orthographic geo-image considering DEM and semantic information

Xingguo Zhang, Shuai Ren, Sen Yang, Mohan Liu, Xiaodi Li
article en

Abstract

Aiming at the problem that it is difficult to accurately calibrate massive Pan-Tilt-Zoom Camera (PTZ) cameras on telecommunication tower and the visualization effect of orthographic geo-image is poor, this paper proposes a new method of realtime orthographic geo-image generating, which is considering Digital Elevation Model (DEM) and semantic information (ROGI-DS). First, through integrating tower cameras with 3D GIS, a camera calibration method based on view fitting (3D GIS-GeoC) is designed. Then, using the trained semantic segmentation model (TCSM), the sky area can automatically be identified and removed. Finally, based on the results of camera calibration and viewshed analysis, and the orthographic geo-image are generated. The results show that: (1) 3D GIS-GeoC method outperforms the traditional Perspective-n-Point (PnP) algorithm;(2) The tower camera semantic segmentation model (TCSM) achieves an accuracy of 96.7%; (3) ROGI-DS method improves the accuracy and visualization of orthographic geo-image under different terrain constraints, and can be used real-time monitoring of natural resources and emergency reliefs.

PLoS ONEVol. 20(5)
Xinyang Normal University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Henan Province, Nanhu Scholars Program for Young Scholars of Xinyang Normal University
Openalex Percentile: Top 86%
Robotics and Sensor-Based Localization
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Video map: A realtime orthographic geo-image considering DEM and semantic information — Xingguo Zhang, Shuai Ren, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS