A Practical Oblivious Map Data Structure with Secure Deletion and History Independence

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map’s semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of geometry, topology and semantics by incorporating the C-Map data structure into the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

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Seismic Noise Attenuation Using Curvelet Transform and Dip Map Data Structure

79th EAGE Conference and Exhibition 2017 ◽

10.3997/2214-4609.201701242 ◽

2017 ◽

Author(s):

T. Nguyen ◽

Y.J. Liu

Keyword(s):

Data Structure ◽

Seismic Noise ◽

Curvelet Transform ◽

Noise Attenuation ◽

Map Data

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A Fast Algebraic Grid Generation Algorithm Base on an Improved Kamaugh Map

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.69-70.670 ◽

2009 ◽

Vol 69-70 ◽

pp. 670-674

Author(s):

Shu Dong Xiu ◽

Shi Jun Ji ◽

Yang Wang

Keyword(s):

Data Structure ◽

Grid Generation ◽

Complex Surface ◽

Algebraic Operation ◽

Generation Algorithm ◽

Spline Surface ◽

Algebraic Formula ◽

Map Data ◽

Algorithm Base ◽

Prototype Design

A fast algebraic grid generation algorithm is proposed and a improved Kamaugh map data structure for the new algorithm is designed in the paper. The new created vertex inside of the region is based on algebraic operation of the corner vertices and the middle vertices of boundary broken lines on the region and the program data structure is a improved Kamaugh map data structure, so the algorithm has the merit of simple algebraic formula, quickly executing speed and powerful technology for the four-sided region enclosed by four broken lines, the algorithm is realized on the four-sided region and B-spline surface on the complex surface. The algorithm is extensively applicable for shape modeling in computer aided geometric design, industrial prototype design and reverse engineering.

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The Map Data Structure

Exploring C++20 ◽

10.1007/978-1-4842-5961-0_15 ◽

2020 ◽

pp. 99-103

Author(s):

Ray Lischner

Keyword(s):

Data Structure ◽

Map Data

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The Photon Map Data Structure

Realistic Image Synthesis Using Photon Mapping ◽

10.1201/b10685-7 ◽

2001 ◽

pp. 67-74

Keyword(s):

Data Structure ◽

Map Data

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The Map Data Structure

Exploring C++ ◽

10.1007/978-1-4302-0352-0_14 ◽

2009 ◽

pp. 99-104

Keyword(s):

Data Structure ◽

Map Data

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Valid Space Description in BIM for 3D Indoor Navigation

Architecture and Design ◽

10.4018/978-1-5225-7314-2.ch025 ◽

2019 ◽

pp. 688-706

Author(s):

Abdoulaye Abou Diakité ◽

Sisi Zlatanova

Keyword(s):

Data Structure ◽

Construction Projects ◽

Indoor Navigation ◽

Spatial Relationships ◽

Map Data ◽

Building Walls ◽

Models Validation ◽

Indoor Spaces ◽

Source Of Information ◽

Space Description

The BIM paradigm, supplied by appropriate standards like IFC, became unavoidable in recent construction projects. Several applications (e.g. indoor navigation, energy analysis ...) find in it a source of information on which they can rely. However, practices reveal that BIM models are not always directly reliable for applications and the latter have to ensure the validity of the data by their own. In the case of indoor navigation, the calculations will highly rely on the IfcSpace objects describing the rooms, in addition to their spatial relationships with their surrounding components. Unfortunately, it is common to face IFC models in which IfcSpace objects contain wrong geometric and topological description. In this paper, the authors discuss the issues related to BIM models validation for indoor navigation. Furthermore, they present a method to generate valid indoor spaces in IFC models. The approach relies on the structural components of the building (walls, slabs, etc.) and uses topological operations, supported by the combinatorial map data structure, to produce watertight space volumes.

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The Map Data Structure

Exploring C++ 11 ◽

10.1007/978-1-4302-6194-0_15 ◽

2013 ◽

pp. 89-94

Author(s):

Ray Lischner

Keyword(s):

Data Structure ◽

Map Data

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Incorporating Topological Representation in 3D City Models

10.20944/preprints201905.0024.v1 ◽

2019 ◽

Author(s):

Stelios Vitalis ◽

Ken Arroyo Ohori ◽

Jantien Stoter

Keyword(s):

Data Structure ◽

Data Model ◽

Semantic Information ◽

Semantic Representation ◽

Geometric Analysis ◽

Computationally Efficient ◽

Real World Data ◽

3D City Models ◽

Map Data ◽

City Models

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map's semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of both geometry, topology and semantics by incorporating the C-Map data structure in the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

Download Full-text