An Efficient Multiresolution Framework for High Quality Interactive Rendering of Massive Point Clouds using Multi-way kd-Trees
Prashant Goswami,
Fatih Erol,
Rahul Mukhi,
Renato Pajarola,
Enrico Gobbetti
Visual Computer, Volume 29, Number 1, page 69--83 - january 2013
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We present an efficient technique for out-of-core multi-resolution construction and high quality interactive visualization of massive point clouds. Our approach
introduces a novel hierarchical level of detail (LOD) organization based on multi-way kd-trees, which simplifies memory management and allows control over the LOD-tree height. The LOD tree, constructed bottom up using a fast high-quality point simplification method, is fully balanced and contains all uniformly sized nodes.
To this end, we introduce and analyze three efficient point simplification approaches that yield a desired number of high-quality output points. For constant rendering performance, we propose an efficient rendering-on-a-budget method with asynchronous data loading, which delivers fully continuous high quality rendering through LOD geo-morphing and deferred blending. Our algorithm is in corporated in a full end-to-end rendering system, which supports both local rendering and cluster-parallel distributed rendering. The method is evaluated on complex models made of hundreds of millions of point samples.
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BibTex references
@Article{GEMPG13,
author = {Goswami, P. and Erol, F. and Mukhi, R. and Pajarola, R. and Gobbetti, E.},
title = {An Efficient Multiresolution Framework for High Quality Interactive Rendering of Massive Point Clouds using Multi-way kd-Trees},
journal = {Visual Computer},
number = {1},
volume = {29},
pages = {69--83},
month = {january},
year = {2013},
keywords = {Point-based rendering; level-of-detail; multi-way kd-tree; entropy-based reduction; clustering; parallel rendering; geo-morphing},
doi = {10.1007/s00371-012-0675-2},
url = {https://publications.crs4.it/pubdocs/2013/GEMPG13},
}
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