AliceVision Meshroom

Griwodz, Carsten; Gasparini, Simone; Calvet, Lilian; Gurdjos, Pierre; Castan, Fabien; Maujean, Benoit; Lillo, Gregoire De; Lanthony, Yann

doi:10.1145/3458305.3478443

Cited by 113 publications

(40 citation statements)

References 43 publications

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“…In the presented two cases, the photogrammetric computation was performed in Meshroom (Griwodz et al, 2021) to generate dense point clouds. Then, point clouds were cropped in MeshLab (Cignoni et al, 2011) manually.…”

Section: Experiments and Resultsmentioning

confidence: 99%

High‐resolution 3‐D geometry updating of digital functional models using point cloud processing and surface cut

Zhang

Xia²,

Taylor

2023

Computer aided Civil Eng

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Point cloud can provide rich 3‐D geometric information of structures, and it has been widely investigated for generating digital functional models, such as finite element (FE) model and building information model (BIM). However, for the existing digital models, how to maintain and update the new local geometric changes on the existing digital models has not been sufficiently studied. Therefore, this research presents a method to update the local 3‐D geometric changes on digital functional models using point cloud processing and surface cut. The proposed pipeline starts from processing the point cloud of the local structural change for reconstructing the local surface mesh. After that, the surface mesh is aligned to the corresponding location of the existing digital model by point cloud registration. Then, the geometry updating can be achieved by cutting the digital model with the generated surface mesh. To validate the proposed geometry updating method, two case studies were performed on damaged concrete beams with their intact FE models. The results show that the 3‐D geometry changes caused by the damage on the edge and vertex can be successfully updated with high resolution on the existing digital models. The results demonstrate the feasibility of integrating the proposed method into structural health monitoring (SHM) systems for further analysis.

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Section: Experiments and Resultsmentioning

confidence: 99%

High‐resolution 3‐D geometry updating of digital functional models using point cloud processing and surface cut

Zhang

Xia²,

Taylor

2023

Computer aided Civil Eng

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“…Although the most intricate three‐dimensional models are still made with computerized tomography (Gignac & Kley, 2014) or laser scans (Szaflik, 2007), photogrammetry allows for a portable and accessible means of creating models (Chiari et al, 2008). Open‐source software can be used to create models of large structures from images taken with off‐the‐shelf aerial vehicles, and models of small objects can be constructed using a phone camera (Griwodz et al, 2021). The general constraint on three‐dimensional photogrammetry is that large numbers of images are required to automatically render accurate models.…”

Section: Figurementioning

confidence: 99%

A three‐dimensional, dynamic blue whale model for research and scientific communication

Segre

Martín²,

Irschick³

et al. 2023

Marine Mammal Science

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“…The software primarily used in this work to produce the point cloud is COLMAP, 26,27 a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) software. While the directions provided in this work reflect the choice of software, many alternative free photogrammetry softwares are available such as Meshroom, 28 MicMac, 29 Multi-View Environment, 30 OpenMVG, 31 Regard3D, 32 and VisualSFM. 33–35 As long as the choice of photogrammetry software can produce geometric data that can be edited and manipulated, the user can proceed to use the described techniques to align and filter data.…”

Section: Photogrammetry Setup For Propellersmentioning

confidence: 99%

Rapid extraction of propeller geometry using photogrammetry

Tang

Chung

2022

International Journal of Micro Air Vehicles

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As small Uninhabited Aerial Vehicles (sUAS) increase in popularity, computational analysis is increasingly being used to model and improve their performance. However, although propeller performance is one of the primary elements in modelling an aircraft, most manufacturers of propellers for this size of vehicle do not publish geometric information for the propeller. The lack of available geometric data makes simulation of propeller aerodynamics challenging. While techniques exist to accurately extract the 3D geometry of a propeller, these methods are often very expensive, time-consuming, or labor intensive. Additionally, typical 3D scanning techniques produce a 3D mesh that is not useful for techniques such as Blade Element Theory (BET), which rely on knowledge of the 2D cross sections along the propeller span. This paper describes a novel workflow to produce point clouds using readily available photo equipment and software and subsequently extract airfoil and propeller blade parameters at specified stations along the propeller span. The described process can be done with little theoretical knowledge of photogrammetry and with minimal human input. The propeller geometry generated is compared against results of established methods of geometry extraction and good agreement is shown.

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AliceVision Meshroom

Cited by 113 publications

References 43 publications

High‐resolution 3‐D geometry updating of digital functional models using point cloud processing and surface cut

High‐resolution 3‐D geometry updating of digital functional models using point cloud processing and surface cut

A three‐dimensional, dynamic blue whale model for research and scientific communication

Rapid extraction of propeller geometry using photogrammetry

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