Interactive Out-of-Core Visualisation of Very Large Landscapes on Commodity Graphics Platform

Cignoni, Paolo; Ganovelli, Fabio; Gobbetti, Enrico; Marton, Fabio; Ponchio, Federico; Scopigno, Roberto

doi:10.1007/978-3-540-40014-1_3

Cited by 10 publications

(9 citation statements)

References 6 publications

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“…The precision for each class is de ned as È Ê AE (4) First of all we verify the validity of the two criteria: the moment of the color and the edge energy based on the anisotropic diffusion. The feature vectors in our method are compared with features that are often used for general image retrieval [8,10]: Table 1 shows the comparison in color.…”

Section: Precision Of Classi Cationmentioning

confidence: 98%

“…Since the data in the 3D map mostly consist of many small, already simpli ed meshes (like buildings made of some cuboids), these simpli cation methods, in which they assume that a single mesh contains a large number of vertices, cannot be applied to it. Although some methods on modeling and rendering of the 3D maps have been already proposed [4][5][6], there exist few methods concerning the reduction of the texture data for the 3D map. In the 3D map, the proportion of the volume of data in texture tends to be much higher than that of geometrical information such as vertices and triangles.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Texture classification and resolution control for 3S urban map

Ueno

Inatsuka²,

Uchino³

et al. 2008

2008 15th IEEE International Conference on Image Processing

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This paper proposes a method to control texture resolution for rendering large-scale 3D urban maps. Recently, performance of computers has been developed rapidly, but it is still hard to directly handle the large-scale 3D maps on PCs, because of its high requirement for hardware capability. Thus the data reduction is essential for rendering of the large map. Since on the 3D maps, texture data, in general, tend to be far larger than geometry data, it is more effective to reduce the texture data by exploiting the LOD (Level of Detail) in order to decrease whole data size. To achieve this, we propose a method to control the resolution of the texture. In our method, the textures are classi ed into some classes. The appropriate texture resolutions are decided according to their rendered sizes on a display and their importance, and the classes they belong to. We verify the validity of our resolution control method by some experiments.

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Section: Precision Of Classi Cationmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Texture classification and resolution control for 3S urban map

Ueno

Inatsuka²,

Uchino³

et al. 2008

2008 15th IEEE International Conference on Image Processing

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“…Cignoni et al [3], [4], [5] have demonstrated the ability to display both adaptive geometry and texture of large terrain data sets in real-time. They utilize a quadtree texture hierarchy and a bintree of triangle patches (TINs) for the geometry.…”

Section: Related Workmentioning

confidence: 99%

Real-time optimal adaptation for planetary geometry and texture: 4-8 tile hierarchies

Hwa

Duchaineau

Joy

2005

IEEE Trans. Visual. Comput. Graphics

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Abstract-The realtime display of huge geometry and imagery databases involves view-dependent approximations, typically through the use of precomputed hierarchies that are selectively refined at runtime. A classic motivating problem is terrain visualization, in which planetary databases involving billions of elevation and color values are displayed on PC graphics hardware at high frame rates. This paper introduces a new diamond data structure for the basic selective-refinement processing, which is a streamlined method of representing the well-known hierarchies of right triangles that have enjoyed much success in realtime, view-dependent terrain display. Regular-grid tiles are proposed as the payload data per diamond for both geometry and texture. The use of 4-8 grid refinement and coarsening schemes allows level-of-detail transitions that are twice as gradual as traditional quadtree-based hierarchies, as well as very high-quality low-pass filtering compared to subsampling-based hierarchies. An out-ofcore storage organization is introduced based on Sierpinski indices per diamond, along with a tile preprocessing framework based on fine-to-coarse, same-level, and coarseto-fine gathering operations. To attain optimal frame-toframe coherence and processing-order priorities, dual split and merge queues are developed similar to the Realtime Optimally Adapting Meshes (ROAM) Algorithm, as well as an adaptation of the ROAM frustum culling technique. Example applications of lake-detection and procedural terrain generation demonstrate the flexibility of the tile processing framework.

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“…With management of large textured landscapes, [19] can realize the visualization of very large models on commodity graphics platforms. Moreover, out-of-core algorithms were also employed in other fields, such as mesh simplification for large complex models [20].…”

Section: Out-of-core Techniquesmentioning

confidence: 99%