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19th International ACM Symposium on 3D Web Technologies

作者： Stein, Christian Limper, Max Kuijper, Arjan Tech Univ Darmstadt Fraunhofer IGD Darmstadt Germany

ISBN: (纸本)9781450330152

The visualization of massive 3D models is an intensively examined field of research. Due to their rapidly growing complexity of such models, visualisation them in real-time will never be possible through a higher speed of rasterization alone. Instead, a practical solution has to reduce the amount of data to be processed, using a fast visibility determination. In recent years, the combination of Javascript and WebGL raised attention for the possibility of rendering hardware-accelerated 3D graphics directly in the browser. However, when compared to desktop applications, they are still fighting with their disadvantages of a generally slower execution speed, or a downgraded set of functionality. We demonstrate the integration of spatial data structures, computed on the client side, using latest technology trends to mitigate the shortcomings of the 3D Web environment. We employ comparably small bounding volume hierarchies to accelerate our visibility determination, as well as to enable specific culling techniques. This allows for an interactive visualization of such massive 3D data sets. Our in-depth analysis of different data structures and environments shows which combination of data structure and visibility determination techniques are currently the best fit for the Web.

关键词： spatial data structures Culling Visibility Determination WebGL X3D X3DOM

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New two-phase spatial data structures with applications to binary images

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2003年第2期14卷 97-113页

作者： Chung, KL Huang, HL Chen, IC Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei 10672 Taiwan

Considering a binary image, a new two-phase representation is presented in this paper to reduce the memory requirement in the conventional tree-based spatial data structures (SDSs) such as the linear quadtree, DF-expression, S-tree representation, etc. Experimental results show that not only our proposed two-phase representation has a better memory-saving effect. but it also can speed up the coding-time when compared to the existing SDSs. We also show that our proposed two-phase representation has a better computational performance when running geometric operations, such as computing the area and the centroid, on the proposed two-phase representation directly. (C) 2003 Elsevier Science (USA). All rights reserved.

关键词： connected component geometric operations image representation spatial data structures

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Some image operations on S-tree-related spatial data structures

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IMAGE AND VISION COMPUTING 1999年第12期17卷 897-904页

作者： Tsai, YH Chung, KL Natl Taiwan Univ Sci & Technol Dept Informat Management Taipei 10672 Taiwan Natl Taiwan Univ Sci & Technol Grad Program Informat Engn Taipei 10672 Taiwan

The S-tree is an efficient spatial data structure for representing binary images. However, for some image operations, such as set, query, and neighbour-finding operations, a linear scan through the entire representation is required. This paper first presents a modified compact S-tree (MCST) for representing binary images. Then, some efficient set, query, and neighbour-finding operations on the MCST are presented. Some experimental results are carried out to demonstrate the computational advantage of the proposed method. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： S-trees spatial data structures image operations set operations query neighbour-finding

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Analysis of spatial data structures for Proximity Detection

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Tsinghua Science and Technology 2008年第S1期13卷 102-107页

作者： Anupreet Walia Jochen Teizer School of Civil and Environmental Engineering Georgia Institute of Technology

Construction is a dangerous business. According to statistics, in every of the past thirteen years more than 1000 workers died in the USA construction industry. In order to minimize the overall number of these incidents, the research presented in this paper investigates to monitor and analyze the trajectories of construction resources first in a simulated environment and later on the actual job site. Due to the complex nature of the construction environment, three dimensional (3D) positioning data of workers is hardly collected. Although technology is available that allows tracking construction assets in real-time, indoors and outdoors, in 3D, at the same time, the continuously changing spatial and temporal arrangement of job sites requires any successfully working data processing system to work in real-time. This research paper focuses is safety on spatial data structures that offer the capability of realigning itself and reporting the distance of the closest neighbor in real-time. This paper presents results to simulations that allow the processing of real-time location data for collision detection and proximity analysis. The presented data structures and perform-ance results to the developed algorithms demonstrate that real-time tracking and proximity detection of resources is feasible.

关键词： proximity detection real-time resource tracking safety spatial data structures work zones

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Satellite Collision Detection using spatial data structures 37

Satellite Collision Detection using Spatial Data Structures

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37th IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Hellwig, Christian Czappe, Fabian Michelt, Martin Bertrandtt, Reinhold Wolf, Felix Tech Univ Darmstadt Dept Comp Sci Darmstadt Germany Tech Univ Darmstadt Inst Flight Syst & Automat Control Darmstadt Germany European Space Agcy ESA ESOC Darmstadt Germany

ISBN: (纸本)9798350337662

In recent years, the number of artificial objects in Earth orbit has increased rapidly due to lower launch costs and new applications for satellites. More and more governments and private companies are discovering space for their own purposes. Private companies are using space as a new business field, launching thousands of satellites into orbit to offer services like worldwide Internet access. Consequently, the probability of collisions and, thus, the degradation of the orbital environment is rapidly increasing. To avoid devastating collisions at an early stage, efficient algorithms are required to identify satellites approaching each other. Traditional deterministic filter-based conjunction detection algorithms compare each satellite to every other satellite and pass them through a chain of orbital filters. Unfortunately, this leads to a runtime complexity of O(n2). In this paper, we propose two alternative approaches that rely on spatial data structures and thus allow us to exploit modern hardware's parallelism efficiently. Firstly, we introduce a purely grid-based variant that relies on non-blocking atomic hash maps to identify conjunctions. Secondly, we present a hybrid method that combines this approach with traditional filter chains. Both implementations make it possible to identify conjunctions in a large population with millions of satellites with high precision in a comparatively short time. While the grid-based variant is characterized by lower memory consumption, the hybrid variant is faster if enough memory is available.

关键词： parallelization spatial data structures conjunction detection orbit space safety space debris

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Efficient user-oriented Pareto fronts and Pareto archives based on spatial data structures

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SWARM AND EVOLUTIONARY COMPUTATION 2021年 65卷

作者： Freitas, Alan Univ Fed Ouro Preto Comp Sci Ouro Preto MG Brazil

YEfficient manipulation of Pareto fronts and Pareto archives involves non-trivial data structures and algorithms. Because of this complexity, researchers and programmers might recur to naive strategies based on linear lists, where most operations require expensive pairwise comparisons between all elements. The lack of a functional container type for Pareto fronts and archives reduces their usefulness in multi-objective optimization, simulations in economics, decision making, data analysis, or any application that caches objects based on multiple criteria. Despite the existence of some frameworks for multi-objective optimization, there is no user-oriented solution focused exclusively on efficient implementations of dynamic fronts and archives as abstract data types with their fundamental operations for insertion, removal, searching, reference points, hyperbox queries, nearest points, and indicators. This paper describes such a library based on spatial data structures for Pareto fronts and archives with specialized algorithms to perform all of these operations with low asymptotic complexity. At a negligible integration cost, the results confirm this implementation achieves notable performance gains over naive methods for fronts of all sizes and dimensions.

关键词： Pareto fronts Pareto archives Multi-Objective optimization Multi-Criteria decision making spatial data structures

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R3MG: R-tree based agglomeration of polytopal grids with applications to multilevel methods

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JOURNAL OF COMPUTATIONAL PHYSICS 2025年 526卷

作者： Feder, Marco Cangiani, Andrea Heltai, Luca Univ Pisa Dept Math Largo Bruno Pontecorvo 5 I-56127 Pisa Italy Int Sch Adv Studies SISSA Math Area MathLab Via Bonomea 265 I-34136 Trieste Italy

We present a novel approach to perform agglomeration of polygonal and polyhedral grids based on spatial indices. Agglomeration strategies are a key ingredient in polytopal methods for PDEs as they are used to generate (hierarchies of) computational grids from an initial grid. spatial indices are specialized data structures that significantly accelerate queries involving spatial relationships in arbitrary space dimensions. We show how the construction of the R-tree spatial database of an arbitrary fine grid offers a natural and efficient agglomeration strategy with the following characteristics: i) the process is fully automated, robust, and dimension-independent, ii) it automatically produces a balanced and nested hierarchy of agglomerates, and iii) the shape of the agglomerates is tightly close to the respective axis aligned bounding boxes. Moreover, the R-tree approach provides a full hierarchy of nested agglomerates which permits fast query and allows for efficient geometric multigrid methods to be applied also to those cases where a hierarchy of grids is not present at construction time. We present several examples based on polygonal discontinuous Galerkin methods, confirming the effectiveness of our approach in the context of challenging three-dimensional geometries and the design of geometric multigrid preconditioners.

关键词： Polytopal grids Agglomeration Discontinuous Galerkin Multilevel methods spatial data structures

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On scalable DCEL overlay operations

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GEOINFORMATICA 2025年 1-38页

作者： Calderon-Romero, Andres Abdelhafeez, Laila Trajcevski, Goce Magdy, Amr Tsotras, Vassilis J. Pontificia Univ Javeriana Dept Syst Engn Calle 40 5-50 Bogota Colombia Univ Calif Riverside Comp Sci Dept 900 Univ Ave Riverside CA 92521 USA Iowa State Univ Dept Elect & Comp Engn 2433 Union Dr Ames IA 50011 USA

The Doubly Connected Edge List (DCEL) is an edge-list structure widely used in spatial applications, primarily for planar topological and geometric computations. However, it is also applicable to various types of data, including 3D models and geographic data. An essential operation is the overlay operation, which combines the DCELs of two input polygon layers and can easily support spatial queries on polygons like the intersection, union, and difference between these layers. However, existing techniques for spatial overlay operations suffer from two main limitations. First, they fail to handle many large datasets practically used in real applications. Second, they cannot handle arbitrary spatial lines that practically form polygons, e.g., city blocks, but they are given as a set of scattered lines. This work proposes a distributed and scalable way to compute the overlay operation and its related supported queries. Our operations also support arbitrary spatial lines through a scalable polygonization process. We address the issues of efficiently distributing the lines and overlay operators and offer various optimizations that improve performance. Our experiments demonstrate that the proposed scalable solution can efficiently compute the overlay of large real datasets.

关键词： spatial data structures Overlay operator DCEL

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Time and space efficient secondary memory representation of quadtrees

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INFORMATION SYSTEMS 1997年第1期22卷 25-37页

作者： Nardelli, E Proietti, G CNR IST ANAL SISTEMI & INFORMAT I-00185 ROME ITALY

Efficient management of spatial data is becoming more and more important and for very large sets of 2-dimensional data, secondary memory data representations are required. An important class of queries for spatial data are those that extract a subset of the data: they are called window queries (also region or range queries). In this paper we propose and analyze a new data structure, namely the hybrid linear quadtree, for the efficient secondary memory processing of three kinds of window queries, that is the exist, the report and the select query. In particular we prove that for a window of size n x n in a feature space (e.g., an image) of size T x T using the hybrid linear quadtree stored on a B+-tree with bucket size r, the exist and report query can be answered with O(nlog(r)T) accesses to secondary storage, while the select query can be answered with O(nlog(r)T+n(2)/r) accesses to secondary storage. This is an improvement in worst-case I/O time complexity over previous results and shows that multiple non-overlapping features (i.e., coloured images) can be treated with the same I/O complexity as single features (i.e., black and white images). Furthermore, we show that the hybrid linear quadtree has a low space occupancy overhead with respect to the classic linear quadtree. (C) 1997 Published by Elsevier Science Ltd.

关键词： spatial data structures quadtrees window queries algorithms

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Bayesian image segmentation using local iso-intensity structural orientation

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2005年第10期14卷 1512-1523页

作者： Wong, WCK Chung, ACS Hong Kong Univ Sci & Technol Lo KweeSeong Med Image Lab Kowloon Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci Kowloon Hong Kong Peoples R China

Image segmentation is a fundamental problem in early computer vision. In segmentation of flat shaded, nontextured objects in real-world images, objects are usually assumed to be piecewise homogeneous. This assumption, however, is not always valid with images such as medical images. As a result, any techniques based on this assumption may produce less-than-satisfactory image segmentation. In this work, we relax the piecewise homogeneous assumption. By assuming that the intensity nonuniformity is smooth in the imaged objects, a novel algorithm that exploits the coherence in the intensity profile to segment objects is proposed. The algorithm uses a novel smoothness prior to improve the quality of image segmentation. The formulation of the prior is based on the coherence of the local structural orientation in the image. The segmentation process is performed in a Bayesian framework. Local structural orientation estimation is obtained with an orientation tensor. Comparisons between the conventional Hessian matrix and the orientation tensor have been conducted. The experimental results on the synthetic images and the real-world images have indicated that our novel segmentation algorithm produces better segmentations than both the global thresholding with the maximum likelihood estimation and the algorithm with the multilevel logistic MRF model.

关键词： biomedical image processing Hessian matrices image segmentation Markov processes maximum a posteriori (MAP) estimation maximum likelihood estimation spatial data structures stochastic fields

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