Compression of 3D Geographical Objects at Various Level of Detail

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43929517" target="_blank" >RIV/49777513:23520/17:43929517 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-45123-7_26" target="_blank" >http://dx.doi.org/10.1007/978-3-319-45123-7_26</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-45123-7_26" target="_blank" >10.1007/978-3-319-45123-7_26</a>

Result language

angličtina

Original language name

Compression of 3D Geographical Objects at Various Level of Detail

Original language description

Compression of 3D objects has been recently discussed mainly in the domain of 3D computer graphics. However, more and more applications demonstrate that the third dimension plays an important role also in the domain of modelling and streaming of geographical objects. This is especially true for 3D city models and their distribution via internet. Despite the fact that compression of textual information related to geographical objects has a significant importance, in this paper we concentrate only on compression of geometry information and also on more complex geometries with irregular shapes. Considering the compression of 3D geographical objects, the 3D triangle meshes representation are used. 3D mesh compression is a way how to reduce the required cost of storage for triangle meshes without losing any details. The triangle is the basic geometric primitive for standard graphics rendering hardware. The compression algorithm aims at storing the input data into a binary file, that is as small as possible. For encoding of the mesh connectivity, our compression implements the popular EdgeBreaker algorithm. The character of geometry encoding is largely governed by the way connectivity is encoded. A popular choice of prediction for the EdgeBreaker algorithm is the parallelogram predictor. It has been observed in (Váša and Brunnett, 2013) that such prediction can be further improved by taking a two-step approach, first transmitting the complete connectivity and only afterwards transmitting the geometry. We used this approach to compress geographical objects at various level of detail. It does not bring an improvement for all datasets, especially meshes with many parallelogram shape prediction stencils do not benefit from it. However for complex geographical objects (bridges in our case) the used algorithm works nicely and after the compression the amount of data is even lower than 4% of the original file size.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

The Rise of Big Spatial Data

ISBN

978-3-319-45122-0

ISSN

1863-2246

e-ISSN

1863-2351

Number of pages

14

Pages from-to

359-372

Publisher name

Springer

Place of publication

Cham

Event location

Ostrava

Event date

Mar 16, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000419321700026