A Mobile Multi-Sensor Platform for Building Reconstruction Integrating Terrestrial and Autonomous Uav-Based Close Range Data Acquisition

Cefalu, Alessandro; Haala, Norbert; Schmohl, Stefan; Neumann, Ingo; Genz, T.

doi:10.5194/isprs-archives-xlii-2-w6-63-2017

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Finally, Open Geospatial Consortium (OGC, 2012) came up with the Level of Detail (LoD) scheme ranging from 0 to 4, which is widely followed in 3D city models. In recent times, the reconstruction of building structures with façade information became a fascinating field of study for survey services (Cefalu, Haala, Schmohl, Neumann, & Genz, 2017). 3D reconstruction of building models has always depended on the point cloud data using ALS.…”

Section: Introductionmentioning

confidence: 99%

Efficient Flight Planning for Building Façade 3d Reconstruction

Palanirajan

Alsadik

Nex

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Three-dimensional (3D) building model is gaining more scientific attention in recent times due to its application in various fields such as vehicle autonomous navigation, urban planning, heritage building documentation, gaming visualisation and tourism. The quality of the Level of Detail (LoD) of building models relies on the high-resolution data sets obtained for the building. As an alternative to laser scanners, Unmanned Aerial Vehicles (UAV) are efficient in collecting good quality images and generate reliable LoD3 of buildings (i.e. to model both roof and facades of a building) at comparatively lower cost and time. However, the complete collection of images on building facades is usually performed by manual flights along the different façade to assure a homogenous image coverage with the same resolution on each element: no offline autonomous procedure to define the main façade planes and acquire complete image sets independent of UAV platform have been developed yet. This paper proposes a novel methodology to generate the flight plan in correspondence of building facades. The Digital Surface Model (DSM) obtained from an initial nadir flight is used as an input to identify the target building and plan the image acquisition around it. The optimised flight plan ensures complete coverage of the building with a minimum number of images. The coordinates as well as the attitude of each planned image can be finally loaded on a UAV to perform the flight. In order to validate the proposed methodology, some tests performed on synthetic buildings of growing complexity and very different shapes are presented.</p>

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Section: Introductionmentioning

confidence: 99%

Efficient Flight Planning for Building Façade 3d Reconstruction

Palanirajan

Alsadik

Nex

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

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“…Algorithms such as Structure-from-Motion and multi-view stereo image matching facilitate the generation of dense meshed point clouds. Authors of [ 41 ] detail an automatic flight mission planning tool, which generates flight lines while aiming at camera configurations, which maintain a roughly constant object distance, provide sufficient image overlap and avoid unnecessary stations, based on a coarse Digital Surface Model and an approximate building outline.…”

Section: Introductionmentioning

confidence: 99%

Drone Mission Definition and Implementation for Automated Infrastructure Inspection Using Airborne Sensors

Besada

Bergesio

Campaña

et al. 2018

Sensors

105

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This paper describes a Mission Definition System and the automated flight process it enables to implement measurement plans for discrete infrastructure inspections using aerial platforms, and specifically multi-rotor drones. The mission definition aims at improving planning efficiency with respect to state-of-the-art waypoint-based techniques, using high-level mission definition primitives and linking them with realistic flight models to simulate the inspection in advance. It also provides flight scripts and measurement plans which can be executed by commercial drones. Its user interfaces facilitate mission definition, pre-flight 3D synthetic mission visualisation and flight evaluation. Results are delivered for a set of representative infrastructure inspection flights, showing the accuracy of the flight prediction tools in actual operations using automated flight control.

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“…Current research contributions by Wujanz et al [ 18 ] show an alternative approach in which the signal strength of the reflected measurement signal and the noise of the distance measurement are linked to derive a stochastic model. The validity of such an intensity-based stochastic model has been demonstrated in several investigations by Wujanz et al [ 18 , 19 ] and was consequently used for various purposes by Cefalu et al [ 20 ] and Xu et al [ 21 ]. Ozendi et al [ 22 ] correctly stated that intensity-based stochastic models can only be used where raw intensity values in the measurement data can be accessed.…”

Section: Introductionmentioning

confidence: 99%

Determination of Intensity-Based Stochastic Models for Terrestrial Laser Scanners Utilising 3D-Point Clouds

Wujanz

Burger

Tschirschwitz

et al. 2018

Sensors

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Recent advances in stochastic modelling of reflectorless rangefinders revealed an inherent relationship among raw intensity values and the corresponding precision of observed distances. In order to derive the stochastic properties of a terrestrial laser scanner’s (TLS) rangefinder, distances have to be observed repeatedly. For this, the TLS of interest has to be operated in the so-called 1D-mode—a functionality which is offered only by a few manufacturers due to laser safety regulations. The article at hand proposes two methodologies to compute intensity-based stochastic models based on capturing geometric primitives in form of planar shapes utilising 3D-point clouds. At first the procedures are applied to a phase-based Zoller + Fröhlich IMAGER 5006h. The generated results are then evaluated by comparing the outcome to the parameters of a stochastic model which has been derived by means of measurements captured in 1D-mode. Another open research question is if intensity-based stochastic models are applicable for other rangefinder types. Therefore, one of the suggested procedures is applied to a Riegl VZ-400i impulse scanner, as well as a Leica ScanStation P40 TLS that deploys a hybrid rangefinder technology. The generated results successfully demonstrate alternative methods for the computation of intensity-based stochastic models as well as their transferability to other rangefinder technologies.

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A Mobile Multi-Sensor Platform for Building Reconstruction Integrating Terrestrial and Autonomous Uav-Based Close Range Data Acquisition

Cited by 4 publications

References 7 publications

Efficient Flight Planning for Building Façade 3d Reconstruction

Efficient Flight Planning for Building Façade 3d Reconstruction

Drone Mission Definition and Implementation for Automated Infrastructure Inspection Using Airborne Sensors

Determination of Intensity-Based Stochastic Models for Terrestrial Laser Scanners Utilising 3D-Point Clouds

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