# Global-Local Airborne Mapping (GLAM): Reconstructing a City from Aerial   Videos

**Authors:** Hasnain Vohra, Maxim Bazik, Matthew Antone, Joseph Mundy, William, Stephenson

arXiv: 1706.01580 · 2018-06-08

## TL;DR

This paper introduces a scalable, real-time visual SLAM system for aerial videos that can reconstruct large city-scale maps with high accuracy using tens of thousands of frames on a standard computer.

## Contribution

The authors present a novel feature-based aerial SLAM system capable of large-area, city-scale mapping with near real-time performance and high accuracy, scalable to tens of thousands of frames.

## Key findings

- Reconstructed city-scale maps with 2-meter accuracy.
- Achieved near real-time processing of 90,000 frames.
- Demonstrated the largest and fastest aerial map reconstruction to date.

## Abstract

Monocular visual SLAM has become an attractive practical approach for robot localization and 3D environment mapping, since cameras are small, lightweight, inexpensive, and produce high-rate, high-resolution data streams. Although numerous robust tools have been developed, most existing systems are designed to operate in terrestrial environments and at relatively small scale (a few thousand frames) due to constraints on computation and storage.   In this paper, we present a feature-based visual SLAM system for aerial video whose simple design permits near real-time operation, and whose scalability permits large-area mapping using tens of thousands of frames, all on a single conventional computer. Our approach consists of two parallel threads: the first incrementally creates small locally consistent submaps and estimates camera poses at video rate; the second aligns these submaps with one another to produce a single globally consistent map via factor graph optimization over both poses and landmarks. Scale drift is minimized through the use of 7-degree-of-freedom similarity transformations during submap alignment.   We quantify our system's performance on both simulated and real data sets, and demonstrate city-scale map reconstruction accurate to within 2 meters using nearly 90,000 aerial video frames - to our knowledge, the largest and fastest such reconstruction to date.

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/1706.01580/full.md

## References

29 references — full list in the complete paper: https://tomesphere.com/paper/1706.01580/full.md

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Source: https://tomesphere.com/paper/1706.01580