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

## TL;DR

This paper introduces a new method for generating accurate and visually improved real-time orthographic geo-images using camera calibration and semantic information.

## Contribution

The novel contribution is the integration of DEM and semantic data to enhance orthographic geo-image generation with real-time capabilities.

## Key findings

- The 3D GIS-GeoC method performs better than the traditional PnP algorithm for camera calibration.
- The TCSM model achieves 96.7% accuracy in identifying and removing sky areas.
- ROGI-DS improves orthographic geo-image accuracy and visualization under various terrains for real-time monitoring.

## 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.