An Incremental Strategy for Fast Transmission of Multi-Resolution Data in a Mobile System

Follin, Jean-Michel; Bouju, Alain

doi:10.1007/978-3-540-37110-6_4

Cited by 2 publications

(1 citation statement)

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“…Multiresolution mesh techniques, including the progressive mesh methods, are focused on highly detailed geometric models and adapt best to certain data types, such as terrain data [10]. However, because these techniques do not consider cartographic simplifications of polygons, they are limited in their ability to implement polygon LoD rendering [11].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Visualization Method for Polygonal Data with Dynamic Simplification

Chen

Zhang

et al. 2018

IJGI

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Polygonal data often require rendering with symbolization and simplification in geovisualization. A common issue in existing methods is that simplification, symbolization and rendering are addressed separately, causing computational and data redundancies that reduce efficiency, especially when handling large complex polygonal data. Here, we present an efficient polygonal data visualization method by organizing the simplification, tessellation and rendering operations into a single mesh generalization process. First, based on the sweep line method, we propose a topology embedded trapezoidal mesh data structure to organize the tessellated polygons. Second, we introduce horizontal and vertical generalization operations to simplify the trapezoidal meshes. Finally, we define a heuristic testing algorithm to efficiently preserve the topological consistency. The method is tested using three OpenStreetMap datasets and compared with the Douglas Peucker algorithm and the Binary Line Generalization tree-based method. The results show that the proposed method improves the rendering efficiency by a factor of six. Efficiency-sensitive mapping applications such as emergency mapping could benefit from this method, which would significantly improve their visualization performances.

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Section: Introductionmentioning

confidence: 99%