Automated Low-Cost Photogrammetry for Flexible Structure Monitoring

Wang, C. H.; Mills, JP; Miller, Pauline E.

doi:10.5194/isprsarchives-xxxix-b5-393-2012

Cited by 10 publications

(7 citation statements)

References 11 publications

(13 reference statements)

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“…Photogrammetric techniques are used to evaluate the structural integrity and characteristics of flexible structures; however, they are often used for evaluative purposes on large structures such as structural beams, underground piping systems and geographical mapping of large areas. [26][27][28] Other structural techniques were considered since there is a body of work looking at approaches other than optical ones [29]; however, these techniques applied to curing concrete offer little benefit in the practical application of a method to evaluate a fast moving membrane sheath such as the waterless trap under a negative pressure. The techniques applied to this research have been developed specifically for this purpose, based on previous work to develop boundary equations for building drainage applications although the techniques were not fully developed in that research [30].…”

Section: Modelling Waterless Trapsmentioning

confidence: 99%

A Photogrammetric Technique for Developing Boundary Equations for Flexible Sheath Waterless Trap Seals as Used in Building Drainage Systems

Jean¹,

Gormley

2021

Buildings

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The water trap seal is still the main method of protecting building inhabitants from the ingress of foul contaminated air and noxious gases from the sewer. This seal can become compromised when water is lost in the trap by processes including evaporation and siphonage from excessive system suction pressures. A recent innovation is the waterless trap seal, which uses flexible sheaths, typically made from silicone rubber to form the seal. The sheath opens in response to a sub-atmospheric air pressure and will shut tightly under a supra-atmospheric pressure in order to form a seal. Full system numerical modelling of building drainage systems has offered insight into system responses to pressure transients and has opened up the evaluation of building wastewater systems to predictive modelling which has assisted in producing improvements to public health. A requirement of any predictive model is a mathematical representation of the physical characteristics of the system. This research develops a technique for developing boundary equations so that predictive modelling is possible. We combine photographic and pressure data analysed by Fourier analysis to develop the model. The technique is applicable to any device were the fluid structure interaction plays a significant role in its operation.

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Section: Modelling Waterless Trapsmentioning

confidence: 99%

A Photogrammetric Technique for Developing Boundary Equations for Flexible Sheath Waterless Trap Seals as Used in Building Drainage Systems

Jean¹,

Gormley

2021

Buildings

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“…The results showed that properly calibrated smartphone cameras can be used for photogrammetric tasks with a required accuracy of 1:10,000. The smartphone SfM photogrammetric method has been tested in many fields including flexible structural monitoring [ 18 ], coastal monitoring [ 19 , 20 , 21 ], auxiliary medical examinations [ 22 , 23 ], alpine alluvial fan surveys [ 24 ], and soil water erosion [ 25 ]. Although the smartphone SfM photogrammetric method has been successfully used in these applications and has produced high-resolution results, to the best of the authors’ knowledge, this approach has rarely been used for mapping the topography of rock joint surfaces in geotechnical laboratories.…”

Section: Introductionmentioning

confidence: 99%

Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry

Fang

Jiang

et al. 2021

Sensors

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The measurement of rock joint surfaces is essential for the estimation of the shear strength of the rock discontinuities in rock engineering. Commonly used techniques for the acquisition of the morphology of the surfaces, such as profilometers and laser scanners, either have low accuracy or high cost. Therefore, a high-speed, low-cost, and high-accuracy method for obtaining the topography of the joint surfaces is necessary. In this paper, a smartphone structure from motion (SfM) photogrammetric solution for measuring rock joint surfaces is presented and evaluated. Image datasets of two rock joint specimens were taken under two different modes by using an iPhone 6s, a Pixel 2, and a T329t and subsequently processed through SfM-based software to obtain 3D models. The technique for measuring rock joint surfaces was evaluated using the root mean square error (RMSE) of the cloud-to-cloud distance and the mean error of the joint roughness coefficient (JRC). The results show that the RMSEs by using the iPhone 6s and Pixel 2 are both less than 0.08 mm. The mean errors of the JRC are −7.54 and −5.27% with point intervals of 0.25 and 1.0 mm, respectively. The smartphone SfM photogrammetric method has comparable accuracy to a 3D laser scanner approach for reconstructing laboratory-sized rock joint surfaces, and it has the potential to become a popular method for measuring rock joint surfaces.

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“…Although their quality is still a limitation for obtaining of highly accurate images, they have the great advantage of being totally portable and are almost always to hand. Currently, they offer a low‐cost option for close‐range photogrammetric applications, including the creation of three‐dimensional (3D) models for a wide range of purposes, including structural monitoring (Wang et al., ), geomorphology (Micheletti et al., ), creative industries (Nocerino et al., ) and medical applications (Abreu de Souza et al., ; Hellwich et al., ; Hernandez & Lemaire, ), among others. Other low‐cost non‐metric cameras, such as webcams, have also been used for close‐range modelling (Chong and Brownstein, ).…”

Section: Introductionmentioning

confidence: 99%

Smartphone‐based close‐range photogrammetric assessment of spherical objects

Barbero-García

Cabrelles

Lerma

et al. 2018

The Photogrammetric Record

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Smartphones have widened the possibilities for low-cost close-range image acquisition for three-dimensional (3D) modelling. They allow the rapid acquisition of large amounts of data for a wide range of applications. However, the accuracy of the models and the automation possibilities depend on the image acquisition conditions and application requirements. In this study, the accuracy and reliability of the derived photogrammetric 3D models are evaluated on a spherical set-up for close-range applications (c.30 cm). Different numbers of images, network configurations, targets, devices and camera calibration methodologies are tested and evaluated. Results show that for this close-range application high accuracy (0Á2 mm) and reliability can be achieved. The number of images did not significantly affect the accuracy but was vital for tie-point detection and image orientation. The use of artificial targets was found to be the key factor in increasing the final accuracy. In contrast, the image calibration strategy and the characteristics of the imaging device did not have a great impact on the results.Smartphone video (more specifically slow-motion video) is a useful tool for acquiring large numbers of images, suitable even for fast moving objects. These images can be used for the creation of 3D models of moving objects (Barbero-Garc ıa et al., 2017). With an image acquisition speed of 240 frames per second (fps) of many smartphones (still far below the ultra-high-speed cameras that reach up to 2000 fps), the computational cost is the main limitation given the number of images to be used for 3D modelling.Despite their advantages, smartphone cameras present high internal instability that hampers their correct calibration. This problem is common to all non-metric digital cameras (Fraser, 2013), but is especially exacerbated when working with smartphones. The radiometric accuracy of smartphone cameras is lower than that of single-lens reflex (SLR) cameras but, despite their limitations, studies have concluded that these cameras can be used for photogrammetric tasks with a required accuracy of 1:10 000 (Akca and Gruen, 2009).The development of useful tools, which could allow non-expert users to obtain accurate 3D models for different purposes, requires a high degree of automation (Remondino et al., 2014). However, most of the available automatic low-cost solutions provide low repeatability and reliability (Remondino et al., 2012). The development of fully automatic and reliable solutions for specific applications requires an extensive knowledge of the factors affecting the quality of the 3D models created using smartphones or other similar imaging devices, such as tablets. The most important factors include the determination of the ideal geometric network, the selection of the best video frames and their optimal number, as well as the accuracy requirements for camera calibration. These parameters can vary greatly depending on the characteristics and limitations of the image acquisition process for a specific application (suc...

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Automated Low-Cost Photogrammetry for Flexible Structure Monitoring

Cited by 10 publications

References 11 publications

A Photogrammetric Technique for Developing Boundary Equations for Flexible Sheath Waterless Trap Seals as Used in Building Drainage Systems

A Photogrammetric Technique for Developing Boundary Equations for Flexible Sheath Waterless Trap Seals as Used in Building Drainage Systems

Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry

Smartphone‐based close‐range photogrammetric assessment of spherical objects

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