Relevant bibliographies by topics / 3D data analysi

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  1. Journal articles

Academic literature on the topic '3D data analysi'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "3D data analysi"

1

Browning, Paul. "MACSPIN: 3D DATA ANALYSIS SOFTWARE." Terra Nova 4, no. 6 (1992): 701–4. http://dx.doi.org/10.1111/j.1365-3121.1992.tb00620.x.

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2

Wu, Youping, and Zhihui Zhou. "Intelligent City 3D Modeling Model Based on Multisource Data Point Cloud Algorithm." Journal of Function Spaces 2022 (July 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/6135829.

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With the rapid development of smart cities, intelligent navigation, and autonomous driving, how to quickly obtain 3D spatial information of urban buildings and build a high-precision 3D fine model has become a key problem to be solved. As the two-dimensional mapping results have constrained various needs in people’s social life, coupled with the concept of digital city and advocacy, making three-dimensional, virtualization and actualization become the common pursuit of people’s goals. However, the original point cloud obtained is always incomplete due to reasons such as occlusion during acquisition and data density decreasing with distance, resulting in extracted boundaries that are often incomplete as well. In this paper, based on the study of current mainstream 3D model data organization methods, geographic grids and map service specifications, and other related technologies, an intelligent urban 3D modeling model based on multisource data point cloud algorithm is designed for the two problems of unified organization and expression of urban multisource 3D model data. A point cloud preprocessing process is also designed: point cloud noise reduction and downsampling to ensure the original point cloud geometry structure remain unchanged, while improving the point cloud quality and reducing the number of point clouds. By outputting to a common 3D format, the 3D model constructed in this paper can be applied to many fields such as urban planning and design, architectural landscape design, urban management, emergency disaster relief, environmental protection, and virtual tourism.
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Wang, Cuixia. "Optimization of Three-Dimensional Model of Landscape Space Based on Big Data Analysis." Journal of Function Spaces 2022 (August 17, 2022): 1–11. http://dx.doi.org/10.1155/2022/7002983.

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Based on virtual reality technology, landscape 3D modeling provides users with the possibility to construct a simulated garden landscape environment design effect online, so it has high requirements for accuracy. With the continuous improvement of precision requirements, the number of people involved in the construction of 3D models is also increasing, which puts forward higher requirements for modeling. Based on this, this paper studies the optimization strategy of landscape space 3D model based on big data analysis. Based on the analysis of the establishment of the 3D model and the related algorithm research, this paper analyzes the optimal design of the 3D model under the background of big data. In the 3D modeling of the edge folded area, it is based on the traditional quadratic error measurement grid simplification algorithm, combined with the vertex error matrix to simplify, so as to shorten the modeling time. Based on an efficient search algorithm, an adaptive nonsearch fractal image compression and decoding method is proposed in the image compression and decoding stage of 3D modeling. The search is performed by specifying the defined area block. Finally, an experiment is designed to analyze the performance of the optimization algorithm. The results show that the improved edge folding region algorithm can reduce errors on the basis of ensuring image quality, and the adaptive search algorithm can shorten the search time and improve the compression rate. This method provides a technical reference for the visualization experience and simulation system of garden landscape design and improves the presentation quality of virtual garden landscape design scenes.
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Deighton, M., and M. Petrou. "Data mining for large scale 3D seismic data analysis." Machine Vision and Applications 20, no. 1 (2007): 11–22. http://dx.doi.org/10.1007/s00138-007-0101-3.

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5

Li, W., S. Zlatanova, and B. Gorte. "VOXEL DATA MANAGEMENT AND ANALYSIS IN POSTGRESQL/POSTGIS UNDER DIFFERENT DATA LAYOUTS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences VI-3/W1-2020 (November 17, 2020): 35–42. http://dx.doi.org/10.5194/isprs-annals-vi-3-w1-2020-35-2020.

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Abstract. Three-dimensional (3D) raster data (also named voxel) is important sources for 3D geo-information applications, which have long been used for modelling continuous phenomena such as geological and medical objects. Our world can be represented in voxels by gridding the 3D space and specifying what each grid represents by attaching every voxel to a real-world object. Nature-triggered disasters can also be modelled in volumetric representation. Unlike point cloud, it is still a lack of wide research on how to efficiently store and manage such semantic 3D raster data. In this work, we would like to investigate four different data layouts for voxel management in open-source (spatial) DBMS - PostgreSQL/PostGIS, which is suitable for efficiently retrieving and quick querying. Besides, a benchmark has been developed to compare various voxel data management solutions concerning functionality and performance. The main test dataset is the groups of buildings of UNSW Kensington Campus, with 10cm resolution. The obtained storage and query results suggest that the presented approach can be successfully used to handle voxel management, semantic and range queries on large voxel dataset.
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Gautier, J., S. Christophe, and M. Brédif. "VISUALIZING 3D CLIMATE DATA IN URBAN 3D MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 781–89. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-781-2020.

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Abstract. In order to understand and explain urban climate, the visual analysis of urban climate data and their relationships with the urban morphology is at stake. This involves partly to co-visualize 3D field climate data, obtained from simulation, with urban 3D models. We propose two ways to visualize and navigate into simulated climate data in urban 3D models, using series of horizontal 2D planes and 3D point clouds. We then explore different parameters regarding transparency, 3D semiologic rules, filtering and animation functions in order to improve the visual analysis of climate data 3D distribution. To achieve this, we apply our propositions to the co-visualization of air temperature data with a 3D urban city model.
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7

Barbu, Viorel, and Michael Röckner. "Global solutions to random 3D vorticity equations for small initial data." Journal of Differential Equations 263, no. 9 (2017): 5395–411. http://dx.doi.org/10.1016/j.jde.2017.06.020.

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8

Papatheodorou, Theodore, John Giannatsis, and Vassilis Dedoussis. "Evaluating 3D Printers Using Data Envelopment Analysis." Applied Sciences 11, no. 9 (2021): 4209. http://dx.doi.org/10.3390/app11094209.

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Data Envelopment Analysis (DEA) is an established powerful mathematical programming technique, which has been employed quite extensively for assessing the efficiency/performance of various physical or virtual and simple or complex production systems, as well as of consumer and industrial products and technologies. The purpose of the present study is to investigate whether DEA may be employed for evaluating the technical efficiency/performance of 3D printers, an advanced manufacturing technology of increasing importance for the manufacturing sector. For this purpose, a representative sample of 3D printers based on Fused Deposition Modeling technology is examined. The technical factors/parameters of 3D printers, which are incorporated in the DEA, are investigated and discussed in detail. DEA evaluation results compare favorably with relevant benchmarks from experts, indicating that the suggested DEA technique in conjunction with technical and expert evaluation could be employed for evaluating the performance of a highly technological system, such as the 3D printer.
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9

Mery, Francisco, Carolina Méndez-Orellana, Javier Torres, et al. "3D simulation of aneurysm clipping: Data analysis." Data in Brief 37 (August 2021): 107258. http://dx.doi.org/10.1016/j.dib.2021.107258.

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10

Plyusnin, Ilya, Alistair R. Evans, Aleksis Karme, Aristides Gionis, and Jukka Jernvall. "Automated 3D Phenotype Analysis Using Data Mining." PLoS ONE 3, no. 3 (2008): e1742. http://dx.doi.org/10.1371/journal.pone.0001742.

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