3d Mapping of Indoor and Outdoor Environments Using Apple Smart Devices

Díaz-Vilariño, L.; Tran, Helena; Frías, Ernesto; Balado, Jesús; Khoshelham, Kourosh

doi:10.5194/isprs-archives-xliii-b4-2022-303-2022

Cited by 25 publications

(19 citation statements)

References 20 publications

(27 reference statements)

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“…The aim of the in situ studies will also be to confirm the results obtained in the laboratory while identifying the errors and to show the limitations of using LiDAR in real conditions. The objective is to propose an experimental protocol based on controlled and field environmental [ 31 ], testing for the evaluation of new smartphone LiDAR sensors in the context of building interior numerisation. This protocol will allow us to provide recommendations for LiDAR smartphone use for a railway station’s indoor building.…”

Section: State Of Artmentioning

confidence: 99%

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Catharia

Richard

Vignoles

et al. 2023

Sensors

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The combination of LiDAR with other technologies for numerisation is increasingly applied in the field of building, design, and geoscience, as it often brings time and cost advantages in 3D data survey processes. In this paper, the reconstruction of 3D point cloud datasets is studied , through an experimental protocol evaluation of new LiDAR sensors on smartphones. To evaluate and analyse the 3D point cloud datasets, different experimental conditions are considered depending on the acquisition mode and the type of object or surface being scanned. The conditions allowing us to obtain the most accurate data are identified and used to propose which acquisition protocol to use. This protocol seems to be the most adapted when using these LiDAR sensors to digitise complex interior buildings such as railway stations. This paper aims to propose: (i) a methodology to suggest the adaptation of an experimental protocol based on factors (distance, luminosity, surface, time, and incidence) to assess the precision and accuracy of the smartphone LiDAR sensor in a controlled environment; (ii) a comparison, both qualitative and quantitative, of smartphone LiDAR data with other traditional 3D scanner alternatives (Faro X130, VLX, and Vz400i) while considering three representative building interior environments; and (iii) a discussion of the results obtained in a controlled and a field environment, making it possible to propose recommendations for the use of the LiDAR smartphone at the end of the numerisation of the interior space of a building.

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Section: State Of Artmentioning

confidence: 99%

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Catharia

Richard

Vignoles

et al. 2023

Sensors

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“…However, with the development of computer vision, sensor technologies, and 3D modelling tools, researchers are increasingly interested in the possibilities of employing entertainment devices like consumer-grade depth cameras [20][21][22][23], smartphones [24][25][26], and augmented reality (AR) headset devices [27][28][29][30] for indoor mapping. While these entertainment devices are not specifically designed for indoor mapping, they are getting a lot of attention in this field because of their advanced sensing technology and highperformance computing, as well as their high degree of portability, which gives them great potential for indoor mapping.…”

Section: Introductionmentioning

confidence: 99%

Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro

Hou,

Hübner,

Schmidt

et al. 2024

Sensors

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Due to their low cost and portability, using entertainment devices for indoor mapping applications has become a hot research topic. However, the impact of user behavior on indoor mapping evaluation with entertainment devices is often overlooked in previous studies. This article aims to assess the indoor mapping performance of entertainment devices under different mapping strategies. We chose two entertainment devices, the HoloLens 2 and iPhone 14 Pro, for our evaluation work. Based on our previous mapping experience and user habits, we defined four simplified indoor mapping strategies: straight-forward mapping (SFM), left–right alternating mapping (LRAM), round-trip straight-forward mapping (RT-SFM), and round-trip left–right alternating mapping (RT-LRAM). First, we acquired triangle mesh data under each strategy with the HoloLens 2 and iPhone 14 Pro. Then, we compared the changes in data completeness and accuracy between the different devices and indoor mapping applications. Our findings show that compared to the iPhone 14 Pro, the triangle mesh accuracy acquired by the HoloLens 2 has more stable performance under different strategies. Notably, the triangle mesh data acquired by the HoloLens 2 under the RT-LRAM strategy can effectively compensate for missing wall and floor surfaces, mainly caused by furniture occlusion and the low frame rate of the depth-sensing camera. However, the iPhone 14 Pro is more efficient in terms of mapping completeness and can acquire a complete triangle mesh more quickly than the HoloLens 2. In summary, choosing an entertainment device for indoor mapping requires a combination of specific needs and scenes. If accuracy and stability are important, the HoloLens 2 is more suitable; if efficiency and completeness are important, the iPhone 14 Pro is better.

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“…In [28], researchers demonstrate the potential and functionality of both sensors in the iPhone and iPad and of some iOS applications (SiteScape, 3DScanner App and EveryPoint). Accuracies are investigated in different relevant scenarios, such as indoor and outdoor, static or dynamic configuration, and in different types of cultural and architectural heritage (e.g., statues, decorated rooms and external facades).…”

Section: Introductionmentioning

confidence: 99%

3D Survey with Apple LiDAR Sensor—Test and Assessment for Architectural and Cultural Heritage

Vacca

2023

Heritage

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The documentation and metric knowledge of architectural and cultural heritage is becoming an increasingly important need, especially concerning the state of degradation of some historical assets and the associated required interventions. In this context, the metric documentation of the investigated heritage becomes fundamental for a complete knowledge of the asset in order to support architects and engineers in the restoration process. Recently, methods and geomatic instrumentation have been developed for the survey of cultural heritage aiming at optimizing costs and time. Apple has integrated into its devices a LiDAR sensor capable of providing a 3D model of spaces and objects. The present paper aims to investigate the potential of this sensor for the production of 3D models of cultural heritage assets in terms of accuracy and applicability. Consistently, four apps developed for the generation of point clouds for five case studies related to architectural-cultural heritage assets have been tested. We used Polycam, Sitescape, 3D Scanner and Scaninverse. The results obtained allow us to conclude that the Apple LiDAR sensor can be used for the creation of 3D models for applications and metric documentation of architectural and cultural heritage that are not particularly complex in form and texture.

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3d Mapping of Indoor and Outdoor Environments Using Apple Smart Devices

Cited by 25 publications

References 20 publications

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Indoor Mapping with Entertainment Devices: Evaluating the Impact of Different Mapping Strategies for Microsoft HoloLens 2 and Apple iPhone 14 Pro

3D Survey with Apple LiDAR Sensor—Test and Assessment for Architectural and Cultural Heritage

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