Comparison Assessment of Digital 3d Models Obtained by Drone-Based Lidar and Drone Imagery

Bouziani, Mourad; Amraoui, Malik; Kellouch, S.

doi:10.5194/isprs-archives-xlvi-4-w5-2021-113-2021

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…They produced a 3D model of the entire area including terrain, buildings, and other details. The other study by Bouziani et al (2021) assessed and confirmed the high accuracy of data from LiDAR (Light Detection and Ranging) drone and photogrammetric drone. Based on this work, it is possible to get high-accuracy fusion-based 3D model from these technologies.…”

Section: Introductionmentioning

confidence: 64%

3d Building Models Development Based on Data Fusion – Current Status

Mutiarasari¹,

Rahman²

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. For the past years, a better and complete 3D building model has been intensely studied. To get a 3D building model as desired, it is known to use data fusion which is a technique of 3D dataset combination. Data fusion is conducted to overcome the limitations of each measurement technique in obtaining data. This paper aims to show the status of 3D building models development that is generated from two or more datasets by using data fusion technique. From several works of data fusion, it is observed the development of data fusion related things like various technologies, methods, and accuracy. The technology used varies for data fusion, for both air and ground based measurements. Technologies such as Terrestrial Laser Scanning (TLS) and close-range photogrammetry are the most appropriate surveying methods to generate accurate and high-resolution models. Meanwhile, recent technology of mobile laser scanning makes scans more quickly and offers more convenience to obtain data in a difficult area. Furthermore, mobile laser scanning has higher completeness data than photogrammetry data. For future work, mobile laser scanning data is be considered to use in data fusion. In term of accuracy, several works agreed that data fusion is a better way to have more complete 3D building models with high accuracy. Related to data processing of data fusion, most of algorithms have disadvantage in accelerating the data fusion time. Therefore, an algorithm to shorten the processing time needs to be created.

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Section: Introductionmentioning

confidence: 64%

3d Building Models Development Based on Data Fusion – Current Status

Mutiarasari¹,

Rahman²

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…In recent years, with the advancement in AI, high-resolution image sensors, and UAVs, photogrammetry has become an economical way for obtaining centimeter-resolution 3D models of buildings, infrastructure, and small objects ( 79 ). Common photogrammetric surveys are developed based on the principle of 3D reconstruction from multiple images and structure-from-motion.…”

Section: Review Of 3d Data Sourcesmentioning

confidence: 99%

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Xu,

Shao,

Chen

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. This paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

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