3-D Multistatic Ground Penetrating Radar Imaging for Augmented Reality Visualization

Pereira, Mayra Caleffi; Burns, Dylan; Orfeo, Daniel; Zhang, Yu; Jiao, Liangbao; Huston, Dryver R.; Xia, Tian

doi:10.1109/tgrs.2020.2968208

Cited by 30 publications

(8 citation statements)

References 22 publications

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“…The major challenge is the localization problem (Pereira et al, 2020), that is, how to guarantee the accuracy of the superimposition to deploy AR technologies. Traditionally, abstaining location information required merging data from blueprints, historical records, dead reckoning, and aboveground sensors, which are time-consuming and lack accuracy (Li et al, 2015).…”

Section: Underground Utilitiesmentioning

confidence: 99%

A Review of Augmented Reality Applications in Civil Infrastructure During the 4th Industrial Revolution

Moreu²

2021

Front. Built Environ.

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The 4th industrial revolution started in 2016 and referred to a new phase in the industrial revolution. One of the most significant technological evolvements during the 4th industrial revolution is Augmented Reality (AR) technology. AR superimposes interactional virtual objects/images to real environments. Because of the interaction and see-through characteristics, AR is better applied to engineering than Virtual Reality (VR). The application of AR in civil infrastructure can avoid artificial mistakes, improve efficiency, and saves budget. This article reviews AR applications in civil infrastructure, focusing on research studies in the latest five years (2016–2020) and their milestone developments. More than half of the AR research and implementation studies have focused on the construction domain in the last five years. Researchers deploy AR technologies in on-site construction to assist in discrepancy checking, collaborative communication, and safety checking. AR also uses building information models (BIMs) to produce detailed 3D structural information for visualization. Additionally, AR has been studied for structural health monitoring (SHM), routine and damage detection, energy performance assessment, crack inspection, excavation, and underground utility maintenance. Finally, AR has also been applied for architecture design, city plan, and disaster prediction as an essential part of smart city service. This article discusses the challenges of AR implementation in civil infrastructure and recommends future applications.

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Section: Underground Utilitiesmentioning

confidence: 99%

A Review of Augmented Reality Applications in Civil Infrastructure During the 4th Industrial Revolution

Moreu²

2021

Front. Built Environ.

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“…Therefore, GPR data reconstruction methods with metric information are popular researched in recent years as well. University of Vermont's research group has published several papers [7], [8] on GPR-based reconstruction using multistatic air-coupled GPR. They first collect the data from different GPR antenna, and further take each obtained gain of GPR data into consideration; moreover, to remove the noise, they also fuse the data with a Hessian-based enhancement filter, which is novel.…”

Section: Introductionmentioning

confidence: 99%

Towards 3D Metric GPR Imaging Based on DNN Noise Removal and Dielectric Estimation

Feng,

Yang,

Xiao

2021

Preprint

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Ground Penetrating Radar (GPR) is one of the most important non-destructive evaluation (NDE) devices to detect the subsurface objects (i.e. rebars, utility pipes) and reveal the underground scene. Due to the background noise and unknown dielectric property of subsurface media, the reconstruction of the subsurface objects with metric information remains the main challenge in GPR inspection. In this letter, a novel metric GPR imaging method is proposed consisting of three steps to address the above challenge. Firstly, a noise removal segmentation model is introduced to clear the GPR raw data; furthermore, a DielectricNet is proposed to predict the dielectric properties of media from each GPR B-scan data and the depth of a target; at the last step, we optimize the back-projection (BP) algorithm by using free motion pattern, thus to obtain the 3D metric BP result. We use both the field and synthetic data to verify the proposed method, experimental results show that our proposed method is able to achieve at least 10% improvement in reconstruction accuracy compared with the conventional BP methods.

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“…In addition, 3D modeling and visualization of underground geohazards can provide continence for geohazards presentation and analysis. With the idea of addressing some of these limitations, some research articles [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] have discussed different ways to visualize the information from underground space. These have made important contributions to the architectural design of underground information systems and the related representation methods of underground structures.…”

Section: Introductionmentioning

confidence: 99%

“…Some works [9,10,17,18,23] used the GPR data to visualize two-dimensional space, but their systems cannot construct intuitive three-dimensional (3D) scenes nor can they assess the countermeasures accurately. Recently, Mauricio [24] proposed a processing workflow of GPR data to create 3D models of subsurface tubular structures, which adopted image reconstruction and enhancement technologies. Other research [11][12][13]16] adopted three-dimensional GPR to construct 3D scenes that used commercial software.…”

Section: Introductionmentioning

confidence: 99%

A Three-Dimensional Visualization Framework for Underground Geohazard Recognition on Urban Road-Facing GPR Data

Wang

Wan

Han

2020

IJGI

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The identification of underground geohazards is always a difficult issue in the field of underground public safety. This study proposes an interactive visualization framework for underground geohazard recognition on urban roads, which constructs a whole recognition workflow by incorporating data collection, preprocessing, modeling, rendering and analyzing. In this framework, two proposed sampling point selection methods have been adopted to enhance the interpolated accuracy for the Kriging algorithm based on ground penetrating radar (GPR) technology. An improved Kriging algorithm was put forward, which applies a particle swarm optimization (PSO) algorithm to optimize the Kriging parameters and adopts in parallel the Compute Unified Device Architecture (CUDA) to run the PSO algorithm on the GPU side in order to raise the interpolated efficiency. Furthermore, a layer-constrained triangulated irregular network algorithm was proposed to construct the 3D geohazard bodies and the space geometry method was used to compute their volume information. The study also presents an implementation system to demonstrate the application of the framework and its related algorithms. This system makes a significant contribution to the demonstration and understanding of underground geohazard recognition in a three-dimensional environment.

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3-D Multistatic Ground Penetrating Radar Imaging for Augmented Reality Visualization

Cited by 30 publications

References 22 publications

A Review of Augmented Reality Applications in Civil Infrastructure During the 4th Industrial Revolution

A Review of Augmented Reality Applications in Civil Infrastructure During the 4th Industrial Revolution

Towards 3D Metric GPR Imaging Based on DNN Noise Removal and Dielectric Estimation

A Three-Dimensional Visualization Framework for Underground Geohazard Recognition on Urban Road-Facing GPR Data

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