Assessment of the trueness and precision of smartphone photogrammetry for rock joint roughness measurement

An, Pengju; Fang, Kun; Zhang, Yi; Jiang, Yaofei; Yang, Yuzhe

doi:10.1016/j.measurement.2021.110598

Cited by 18 publications

(6 citation statements)

References 40 publications

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“…Digital photogrammetry and LiDAR-based geospatial field data acquisition using smartphones and tablets is revolutionizing the use of close-range 3D remote sensing within the geosciences [1][2][3][4][5][6][7]. Commensurately, the rapid uptake of low-cost, readily deployable multi-senor drones has extended the reach of such techniques, enabling nadir view photogrammetric surveys of horizontal outcrops, as well as occlusion free reconstructions of large vertical sections [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Benchmarking Different SfM-MVS Photogrammetric and iOS LiDAR Acquisition Methods for the Digital Preservation of a Short-Lived Excavation: A Case Study from an Area of Sinkhole Related Subsidence

et al. 2022

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We are witnessing a digital revolution in geoscientific field data collection and data sharing, driven by the availability of low-cost sensory platforms capable of generating accurate surface reconstructions as well as the proliferation of apps and repositories which can leverage their data products. Whilst the wider proliferation of 3D close-range remote sensing applications is welcome, improved accessibility is often at the expense of model accuracy. To test the accuracy of consumer-grade close-range 3D model acquisition platforms commonly employed for geo-documentation, we have mapped a 20-m-wide trench using aerial and terrestrial photogrammetry, as well as iOS LiDAR. The latter was used to map the trench using both the 3D Scanner App and PIX4Dcatch applications. Comparative analysis suggests that only in optimal scenarios can geotagged field-based photographs alone result in models with acceptable scaling errors, though even in these cases, the orientation of the transformed model is not sufficiently accurate for most geoscientific applications requiring structural metric data. The apps tested for iOS LiDAR acquisition were able to produce accurately scaled models, though surface deformations caused by simultaneous localization and mapping (SLAM) errors are present. Finally, of the tested apps, PIX4Dcatch is the iOS LiDAR acquisition tool able to produce correctly oriented models.

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Section: Introductionmentioning

confidence: 99%

Benchmarking Different SfM-MVS Photogrammetric and iOS LiDAR Acquisition Methods for the Digital Preservation of a Short-Lived Excavation: A Case Study from an Area of Sinkhole Related Subsidence

et al. 2022

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“…To achieve acceptable trueness and precision, the smartphone photogrammetry method can be used. [14] Furthermore, the dense clouds of the digital camera had a higher point density nearly three times that of the smartphone. This difference resulted in better geometrical detail representation and higher mesh quality.…”

Section: Literature Reviewmentioning

confidence: 99%

Development and Creation of Ancient Sandstone Carvings Using 3D Software Tools and Mobile/Tablet Devices

Sookkaew,

Kaenmueang,

Chaikaew

2023

Int. J. Interact. Mob. Technol.

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In the area of Phayao Province that used to be part of the ancient Lanna Kingdom, there are unique works of art that can be found until today, which are sandstone carvings caused by religious beliefs resulting in works such as Buddha statues. These are art related to religion. Nowadays, these works of art have started to fade away and receive less and less attention from people. The creation of art objects in this research therefore uses the interpretation of the creative objects in line with people’s lifestyles by selecting the lotus, which is a plant related to rivers, and is important in religion. In the lotus, which is interconnected and aligned with Buddhism, and in harmony with a way of life that aligns with the river, creative works are found in various forms, connecting people in Buddhism, including sandstone carving. In this creation, digital technology tools and methods are used to collect data to create a 3D work piece. Photogrammetry is used to record detailed proportions and information and customization of 3D work pieces. In these steps, mobile phone-type tools are used to collect image data to create the 3D work or an application is used to customize 3D work pieces from a tablet device to create prototypes of sandstone sculptures from the artisans that remain today. This can be seen in creating, maintaining, and recording digital data, creation, and the integration of knowledge. This demonstrates that today’s tools and portable devices can help create more creative pieces of work and preserve art and culture.

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“…The point cloud data size is a major limitation as it can increase the computational cost. Ozturk et al [22], Chen and Jiang [23], and An et al [24] determined rock discontinuities using mobile phone images, which is also a practical approach depending on the size of the region to be imaged and the rock mass parameters. All studies mentioned above rely on point clouds for detecting rock mass discontinuities.…”

Section: Introductionmentioning

confidence: 99%

A Novel Rock Mass Discontinuity Detection Approach with CNNs and Multi-View Image Augmentation

Yalcin,

Can,

Gokceoglu

et al. 2024

IJGI

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Discontinuity is a key element used by geoscientists and civil engineers to characterize rock masses. The traditional approach to detecting and measuring rock discontinuity relies on fieldwork, which poses dangers to human life. Photogrammetric pattern recognition and 3D measurement techniques offer new possibilities without direct contact with rock masses. This study proposes a new approach to detect discontinuities using close-range photogrammetric techniques and convolutional neural networks (CNNs) trained on a small amount of data. Investigations were conducted on basalts in Bala, Ankara, Türkiye. A total of 34 multi-view images were collected with a remotely piloted aircraft system (RPAS), and discontinuity lines were manually delineated on a point cloud generated from these images. The lines were back-projected onto the raw images to increase the amount of data, a process we call multi-view (3D) augmentation. We further evaluated radiometric and geometric augmentation methods, the contribution of multi-view augmentation to the proposed model, and the transfer learning performance of six different CNN architectures. The highest performance was achieved with U-Net + SE-ResNeXt-50 with an F1-score of 90.6%. The CNN model trained from scratch with local features also yielded a similar F1-score (91.7%), which is the highest performance reported in the literature.

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Assessment of the trueness and precision of smartphone photogrammetry for rock joint roughness measurement

Cited by 18 publications

References 40 publications

Benchmarking Different SfM-MVS Photogrammetric and iOS LiDAR Acquisition Methods for the Digital Preservation of a Short-Lived Excavation: A Case Study from an Area of Sinkhole Related Subsidence

Benchmarking Different SfM-MVS Photogrammetric and iOS LiDAR Acquisition Methods for the Digital Preservation of a Short-Lived Excavation: A Case Study from an Area of Sinkhole Related Subsidence

Development and Creation of Ancient Sandstone Carvings Using 3D Software Tools and Mobile/Tablet Devices

A Novel Rock Mass Discontinuity Detection Approach with CNNs and Multi-View Image Augmentation

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