Zipper: A compact connectivity data structure for triangle meshes

Gurung, Topraj; Luffel, Mark; Lindström, Peter; Rossignac, Jarek

doi:10.1016/j.cad.2012.10.009

Cited by 21 publications

(15 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A compact yet fully connected data structure is the requirement for storage efficient representation of TINs. The requirement for storage efficient representations for triangular meshes has resulted in a number of compression methods and light weight data structures like SQuad (Gurung et al, 2011a), Grouper (Luffel et al, 2014), Laced Ring (LR) (Gurung et al, 2011b), Zipper (Gurung et al, 2013), and Tripod (Snoeyink and Speckmann, 1999). These data structures just stores a set of core links from which other links can be inferred.…”

Section: Resultsmentioning

confidence: 99%

Comparative Analysis of Data Structures for Storing Massive Tins in a DBMS

Kumar¹,

Ledoux²,

Stoter³

2016

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

View full text Add to dashboard Cite

ABSTRACT:Point cloud data are an important source for 3D geoinformation. Modern day 3D data acquisition and processing techniques such as airborne laser scanning and multi-beam echosounding generate billions of 3D points for simply an area of few square kilometers. With the size of the point clouds exceeding the billion mark for even a small area, there is a need for their efficient storage and management. These point clouds are sometimes associated with attributes and constraints as well. Storing billions of 3D points is currently possible which is confirmed by the initial implementations in Oracle Spatial SDO PC and the PostgreSQL Point Cloud extension. But to be able to analyse and extract useful information from point clouds, we need more than just points i.e. we require the surface defined by these points in space. There are different ways to represent surfaces in GIS including grids, TINs, boundary representations, etc. In this study, we investigate the database solutions for the storage and management of massive TINs. The classical (face and edge based) and compact (star based) data structures are discussed at length with reference to their structure, advantages and limitations in handling massive triangulations and are compared with the current solution of PostGIS Simple Feature. The main test dataset is the TIN generated from third national elevation model of the Netherlands (AHN3) with a point density of over 10 points/m 2 . PostgreSQL/PostGIS DBMS is used for storing the generated TIN. The data structures are tested with the generated TIN models to account for their geometry, topology, storage, indexing, and loading time in a database. Our study is useful in identifying what are the limitations of the existing data structures for storing massive TINs and what is required to optimise these structures for managing massive triangulations in a database.

show abstract

Section: Resultsmentioning

confidence: 99%

Comparative Analysis of Data Structures for Storing Massive Tins in a DBMS

Kumar¹,

Ledoux²,

Stoter³

2016

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

View full text Add to dashboard Cite

show abstract

“…This convergence is already starting to take place; for instance, very recent compact data structures are now getting close to the bit rate of pure compression approaches [Gurung et al 2013] and/or support data parallel processing and streamed out-of-core access [Luffel et al 2014]. Random access compression methods may also be seen as hybrid between these three fields of research.…”

Section: Evolution Of the Fieldmentioning

confidence: 98%

“…The principle is to reorder the vertices along a nearly Hamiltonian cycle (called the ring). The same authors then introduced the improved Zipper approach [Gurung et al 2013], which is able to store only six bits per triangle, mostly thanks to differential coding of the vertex indices and improved ring construction. Table III summarizes the most relevant approaches.…”

Section: Compact Representationmentioning

confidence: 99%

3D Mesh Compression

Maglo¹,

et al. 2015

View full text Add to dashboard Cite

3D meshes are commonly used to represent virtual surface and volumes. However, their raw data representations take a large amount of space. Hence, 3D mesh compression has been an active research topic since the mid 1990s. In 2005, two very good review articles describing the pioneering works were published. Yet, new technologies have emerged since then. In this article, we summarize the early works and put the focus on these novel approaches. We classify and describe the algorithms, evaluate their performance, and provide synthetic comparisons. We also outline the emerging trends for future research.

show abstract

“…The need for storage‐efficient representations for triangular meshes has contributed to the development of a number of compact data structures which have different goals, such as compression and/or explicit storage of topological relationships, for example Indexed Triangles (similar to OBJ), Triangles with adjacency information (referred to here as Triangle+) (Shewchuk, ; Boissonnat, Devillers, Pion, Teillaud, & Yvinec, ), Stars (Blandford, Blelloch, Cardoze, & Kadow, ; Ledoux, ), TriStrips (Speckmann & Snoeyink, ), Half‐edge or DCEL (Muller & Preparata, ; Mäntylä, ), SQuad (Gurung, Laney, Lindstrom, & Rossignac, ), Grouper (Luffel, Gurung, Lindstrom, & Rossignac, ), Laced Ring (Gurung, Luffel, Lindstrom, & Rossignac, ), Zipper (Gurung, Luffel, Lindstrom, & Rossignac, ), and Tripod (Snoeyink & Speckmann, ).…”

Section: State‐of‐the‐art In Modeling Terrains With Tinsmentioning

confidence: 99%

Compactly representing massive terrain models as TINs in CityGML

Kumar

Ledoux

Stoter

2018

Transactions in GIS

View full text Add to dashboard Cite

Terrains form an important part of 3D city models. GIS practitioners often model terrains with 2D grids. However, TINs (Triangulated Irregular networks) are also increasingly used in practice. One such example is the 3D city model of the Netherlands (3DTOP10NL), which covers the whole country as one massive triangulation with more than one billion triangles. Due to the massive size of terrain datasets, the main issue is how to efficiently store and maintain them. The international 3D GIS standard CityGML allows us to store TINs using the Simple Feature representation. However, we argue that it is not appropriate for storing massive TINs and has limitations. We focus in this article on an improved storage representation for massive terrain models as TINs. We review different data structures for compactly representing TINs and explore how they can be implemented in CityGML as an ADE (Application Domain Extension) to efficiently store massive terrains. We model our extension using UML, and XML schemas for the extension are automatically derived from these UML models. Experiments with massive real‐world terrains show that, with this approach, we can compress CityGML files up to a factor of ~20 with one billion+ triangles, and our method has the added benefit of explicitly storing the topological relationships of a TIN model.

show abstract

Zipper: A compact connectivity data structure for triangle meshes

Cited by 21 publications

References 17 publications

Comparative Analysis of Data Structures for Storing Massive Tins in a DBMS

Comparative Analysis of Data Structures for Storing Massive Tins in a DBMS

3D Mesh Compression

Compactly representing massive terrain models as TINs in CityGML

Contact Info

Product

Resources

About