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Autori principali: Brodsky, Dmitry, Watson, Benjamin
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2507.15186
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author Brodsky, Dmitry
Watson, Benjamin
author_facet Brodsky, Dmitry
Watson, Benjamin
contents As modeling and visualization applications proliferate, there arises a need to simplify large polygonal models at interactive rates. Unfortunately existing polygon mesh simplification algorithms are not well suited for this task because they are either too slow (requiring the simplified model to be pre-computed) or produce models that are too poor in quality. These shortcomings become particularly acute when models are extremely large. We present an algorithm suitable for simplification of large models at interactive speeds. The algorithm is fast and can guarantee displayable results within a given time limit. Results also have good quality. Inspired by splitting algorithms from vector quantization literature, we simplify models in reverse, beginning with an extremely coarse approximation and refining it. Approximations of surface curvature guide the simplification process. Previously produced simplifications can be further refined by using them as input to the algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2507_15186
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Model Simplification through refinement
Brodsky, Dmitry
Watson, Benjamin
Graphics
As modeling and visualization applications proliferate, there arises a need to simplify large polygonal models at interactive rates. Unfortunately existing polygon mesh simplification algorithms are not well suited for this task because they are either too slow (requiring the simplified model to be pre-computed) or produce models that are too poor in quality. These shortcomings become particularly acute when models are extremely large. We present an algorithm suitable for simplification of large models at interactive speeds. The algorithm is fast and can guarantee displayable results within a given time limit. Results also have good quality. Inspired by splitting algorithms from vector quantization literature, we simplify models in reverse, beginning with an extremely coarse approximation and refining it. Approximations of surface curvature guide the simplification process. Previously produced simplifications can be further refined by using them as input to the algorithm.
title Model Simplification through refinement
topic Graphics
url https://arxiv.org/abs/2507.15186