Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System), also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.

A V-SLAM Guided and Portable System for Photogrammetric Applications

Alessandro Torresani;Fabio Menna;Roberto Battisti;Fabio Remondino
2021-01-01

Abstract

Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System), also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/330911
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