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10th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Chen, Jiaxi Fang, Wei Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9781728109459

In order to meet the requirements of large-scale 3D scene transmission, parsing and real-time visualization in the Web environment, a kind of data structure is proposed in this paper, which specifies the logical structure and physical storage format of the 3D spatial data, and can effectively divide and index the 3D scene. Meanwhile, based on the existing spatial index technology, we propose a hybrid index structure R*O-tree which combines the W-tree and the R*-tree to improve the performance. The experimental results show that the proposed data structure can save about 60%-80% disk space, and the improved index structure is more efficient. Our method is more advantageous than the traditional three-dimensional spatial data structure.

关键词： spatial data structure spatial index R*O-tree Web3DGIS

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Nested spatial data structures for optimal indexing of LiDAR data

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2023年 195卷 287-297页

作者： Ogayar-Anguita, Carlos J. Lopez-Ruiz, Alfonso Rueda-Ruiz, Antonio J. Segura-Sanchez, Rafael J. Univ Jaen Dept Comp Sci EPS Jaen Jaen 23071 Spain

In this paper we present a flexible framework for creating spatial data structures to manage LiDAR point clouds in the context of spatial big data. For this purpose, standard approaches typically include the use of a single data structure to index point clouds. Some of them use a hybrid two-tier solution to optimize specific application purposes such as storage or rendering. In this article we introduce a meta-structure that can have unlimited depth and a custom, user-defined combination of nested structures, such as grids, quadtrees, octrees, or kd-trees. With our approach, the out-of-core indexing of point clouds can be adapted to different types of datasets, taking into account the spatial distribution of the data. Therefore, the most suitable spatial indexing can be achieved for any type of dataset, from small TLS-based scenes to planetary-scale ALS-based scenes. This approach allows us to work with overlapping datasets of different resolutions from different acquisition technologies in the same structure.

关键词： spatial data structure spatial big data Ubiquitous Point Cloud LiDAR

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Combinatorial and asymptotic results on the neighborhood grid

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DISCRETE APPLIED MATHEMATICS 2025年 372卷 48-64页

作者： McDonough, Alex Reitebuch, Ulrich Skrodzki, Martin Univ Oregon Eugene OR USA FU Berlin Math & Comp Sci Berlin Germany Delft Univ Technol Comp Graph & Visualizat Delft Netherlands

In various application fields, such as fluid-, cell-, or crowd-simulations, spatial data structures are very important. They answer nearest neighbor queries which are instrumental in performing necessary computations for, e.g., taking the next time step in the simulation. Correspondingly, various such data structures have been developed, one being the neighborhood grid. In this paper, we consider combinatorial aspects of this data structure. Particularly, we show that an assumption on uniqueness, made in previous works, is not actually satisfied. We extend the notions of the neighborhood grid to arbitrary grid sizes and dimensions and provide two alternative, correct versions of the proof that was broken by the dissatisfied assumption. Furthermore, we explore both the uniqueness of certain states of the data structure as well as when the number of these states is maximized. We provide a partial classification by using the hook-length formula for rectangular Young tableaux. Finally, we conjecture how to extend this to all 2-dimensional cases. (c) 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Neighborhood grid Uniqueness Asymptotic Young tableaux spatial data structure

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SPSLiDAR: towards a multi-purpose repository for large scale LiDAR datasets

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2022年第5期36卷 992-1011页

作者： Rueda-Ruiz, Antonio J. Ogayar-Anguita, Carlos J. Segura-Sanchez, Rafael J. Bejar-Martos, Juan A. Delgado-Garcia, Jorge Univ Jaen CEATIC Jaen 23071 Spain

The widespread use of LiDAR technology in a multitude of domains has produced a growing availability of massive high-resolution point datasets that demand new approaches for efficient organization and storage, filtering using different spatio-temporal criteria, selective/progressive visualization, processing and analysis, and collaborative editing. Ideally, LiDAR data coming from multiple sources and organized in different datasets should be accessible in a simple, uniform, and ubiquitous way to comply with the FAIR principle proposed by the Open Geospatial Consortium: Findable, Accessible, Interoperable, and Reusable. With this goal in mind, we present SPSLiDAR, a conceptual model with a simple interface for repositories of LiDAR data that can be adapted to the needs of different applications. SPSLiDAR includes aspects, such as the arrangement of related datasets into workspaces on a world scale, support for overlapping datasets with different resolutions or acquired at different times, and hierarchical organization of point data, enabling levels of detail and selective download. We also describe in detail an implementation of this model aimed at visualization and downloading of large datasets using the MongoDB database. Finally, we show some experimental results of this implementation using real data, such as its space requirements, upload latency, access latency, and throughput.

关键词： LiDAR big data point cloud spatial data structure NoSQL

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A Novel Scene Management Technology for Complex Virtual Battlefield Environment 9

A Novel Scene Management Technology for Complex Virtual Batt...

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9th International Conference on Graphic and Image Processing (ICGIP)

作者： Sheng, Changchong Jiang, Libing Tang, Bo Tang, Xiaoan Natl Univ Def Technol Changsha 410073 Hunan Peoples R China

ISBN: (数字)9781510617421

ISBN: (纸本)9781510617421

The efficient scene management of virtual environment is an important research content of computer real-time visualization, which has a decisive influence on the efficiency of drawing. However, Traditional scene management methods do not suitable for complex virtual battlefield environments, this paper combines the advantages of traditional scene graph technology and spatial data structure method, using the idea of management and rendering separation, a loose object-oriented scene graph structure is established to manage the entity model data in the scene, and the performance-based quad-tree structure is created for traversing and rendering. In addition, the collaborative update relationship between the above two structural trees is designed to achieve efficient scene management. Compared with the previous scene management method, this method is more efficient and meets the needs of real-time visualization.

关键词： Scene management real-time visualization virtual battlefield environment scene graph spatial data structure

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Accelerated Single Ray Tracing for Wide Vector Units 17

Accelerated Single Ray Tracing for Wide Vector Units

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High-Performance Graphics (HPG) Conference

作者： Fuetterling, Valentin Lojewski, Carsten Pfreundt, Franz-Josef Hamann, Bernd Ebert, Achim Fraunhofer ITWM Competence Ctr High Performance Comp Kaiserslautern Germany Univ Calif Davis Dept Comp Sci Davis CA 95616 USA Univ Kaiserslautern Dept Comp Sci Kaiserslautern Germany

ISBN: (纸本)9781450351010

Utilizing the vector units of current processors for ray tracing single rays through Bounding Volume Hierarchies has been accomplished by increasing the branching factor of the acceleration structure to match the vector width. A high branching factor allows vectorized bounding box tests but requires a complex control flow for the calculation of a front-to-back traversal order. We propose a novel algorithm for single rays entirely based on vector operations that performs a complete traversal iteration in constant time, ideally suited for current and future micro architectures featuring wide vector units. In addition we use our single ray technique as a building block to construct a fast packet traversal for coherent rays. We validate our algorithms with implementations utilizing the AVX2 and AVX-512 instruction sets and demonstrate significant performance gains over state-of-the-art solutions.

关键词： ray tracing spatial data structure bounding volume hierarchy vectorized data processing

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Toward Real-Time Ray Tracing: A Survey on Hardware Acceleration and Microarchitecture Techniques

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ACM COMPUTING SURVEYS 2017年第4期50卷 58-58页

作者： Deng, Yangdong Ni, Yufei Li, Zonghui Mu, Shuai Zhang, Wenjun Tsinghua Univ Sch Software Engn Beijing Peoples R China Tsinghua Univ Inst Microelect Beijing Peoples R China Qualcomm San Diego CA USA

Ray tracing has long been considered as the next-generation technology for graphics rendering. Recently, there has been strong momentum to adopt ray tracing-based rendering techniques on consumer-level platforms due to the inability of further enhancing user experience by increasing display resolution. On the other hand, the computing workload of ray tracing is still overwhelming. A 10-fold performance gap has to be narrowed for real-time applications, even on the latest graphics processing units (GPUs). As a result, hardware acceleration techniques are critical to delivering a satisfying level performance while at the same time meeting an acceptable power budget. A large body of research on ray-tracing hardware has been proposed over the past decade. This article is aimed at providing a timely survey on hardware techniques to accelerate the ray-tracing algorithm. First, a quantitative profiling on the ray-tracing workload is presented. We then review hardware techniques for the main functional blocks in a ray-tracing pipeline. On such a basis, the ray-tracing microarchitectures for both ASIC and processors are surveyed by following a systematic taxonomy.

关键词： Design Algorithms Performance Ray tracing GPU spatial data structure construction traversal

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A Hybrid 3D spatial data structure for the Integration of Aboveground, Ground and Underground Objects

A Hybrid 3D Spatial Data Structure for the Integration of Ab...

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18th International Conference on Geoinformatics

作者： Shen, Jingwei Lv, Guonian Wen, Yongning Wu, Mingguang Zhang, Hongping Wang, Xiao Nanjing Normal Univ Key Lab Virtual Geog Environm Minist Educ Nanjing 210046 Jiangsu Provinc Peoples R China

ISBN: (纸本)9781424473021

A hybrid 3D spatial data structure for the integration of aboveground, ground and underground objects based on spatial cognition theory is proposed, which considers the space subdivision and topology completeness. Object-oriented method is used to abstract objects in real world which is defined into three levels. Geometry primitives and topology primitives are defined in this data structure. Topology is the option of the geometry. The geometry information can be coded in a binary method to store in the relation database. An experiment is designed to integrate the buildings, terrain, and geological stratification seamlessly. The data structure could express aboveground, ground and underground objects effectively.

关键词： spatial data structure Object-Oriented Method Aboveground Ground and Underground Integration Seamlessly

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Non-recursive Inorder Traversal on Constructed Threaded K-D Tree for Efficient Cloud Based Space Partitioning 2

Non-recursive Inorder Traversal on Constructed Threaded K-D ...

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International Conference on Advances in Computer Engineering and Applications (ICACEA)

作者： Roy, Sandip Bose, Rajesh Sarddar, Debabrata Univ Kalyani Dept CSE Kalyani W Bengal India

ISBN: (纸本)9781467369114

Cloud computing system comprises of a set of cloud nodes scattered over a large geographical surface. These cloud nodes usually helps to handle efficiently a new arrived job in cloud system. Now a day's researchers used to work for logically partitioning the earth surface such that every partition contains at least one cloud node which will be prime dedicated for handling jobs arrived in that partition. This phenomenon of partitioning the cloud system is called as 'Cloud Division Rule'. Using spatial data structure we have recursively broken down the earth surface in small zone, namely cloud cluster, containing single cloud node. For getting nodes' information (like load status, network bandwidth etc.) from the master cloud node traversing all the child cloud node is one of the way. Traversal of each cloud node is recursively performed in order to provide some services to users' request in considered cloud system. As millions of cloud nodes over the earth surface are to be clustered and recursively traversed, so a huge number of stack space and stack operations are internally initiated. To optimize these operations we have constructed a threaded k-d tree and do non-recursive inorder traversal over it. This novel approach makes the searching of ancestor and descendant cloud nodes from the current cloud node very easy and also optimizes the computation time and internal memory space of the computation unit which is one of the prime aspect for today's cloud computing Infrastructure as a Service (IaaS).

关键词： Cloud computing cloud partitioning infrastructure as a service non-recursive inorder traversal spatial data structure

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Soil heterogeneity characterization using PCA (X_variogram) - Multivariate analysis of spatial signatures for optimal sampling purposes

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2014年 136卷 24-35页

作者： Kardanpour, Zahra. Jacobsen, Ole Stig Esbensen, Kim H. Geol Survey Denmark & Greenland GEUS Copenhagen Denmark Aalborg Univ ACABS Res Grp Aalborg Denmark Telemark Univ Coll Porsgrunn Norway

This study explores how to combine variographic spatial characterization with multivariate data analysis, by showing how Principal Component Analysis (PCA) can be applied to unconventional types of data matrices, X-variogram. This is here performed on a specific data set from an agricultural field in western Jutland, Denmark, but the data analytical approach is generic. In order to characterize the heterogeneity of a typical sandy soil, a variographic experiment along a 1-D profile is performed on 38 different minerogenic variables (geochemical elements). While the variogram is defined for one variable only, it is shown how PCA is able to characterize a multitude of variograms simultaneously, facilitating subject-matter interpretation of the fingerprints of the process(es) responsible for the spatial heterogeneity encountered. PCA scores and loadings contain information pertaining to the specific matrix type consisting of variograms, X-variogram. Together with a companion paper, a complete approach for characterizing scale-varying spatial heterogeneity is presented with a view of developing sampling procedures for managing the intrinsic variability in natural soil and in similar systems (e.g. environmental characterization and monitoring, pollution in time and space, applied geochemistry, medical geology). Sampling in all of these contexts is shown to be much more than a 'materials handling' issue, by force involving the Theory of Sampling, TOS. The PCA (X-variogram) approach can be applied for tuning in of sampling procedures and 1-D and 2-D sampling plans in soil, environmental substrates, pollution and medical geology studies with a carrying-over potential to many other application fields with similar heterogeneity management needs. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Variogram Heterogeneity characterization Heterogeneity management Scale dependency Representative sampling spatial data structure Fate studies

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