User-controlled simplification of polygonal models

M. Hussain, Y. Okada, K. Niijima
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引用次数: 3

Abstract

Polygonal models are ubiquitous in computer graphics but their real time manipulation and rendering especially in interactive application environments have become a threat because of their huge sizes and complexity. A whole family of automatic algorithms emerged during the last decade to help out this problem, but they reduce the complexity of the models uniformly without caring about semantic importance of localized parts of a mesh. Only a few algorithms deal with adaptive simplification of polygonal models. We propose a new model for user-driven simplification exploiting the simplification hierarchy and hypertriangulation model [P. Cignoni et al.] that lends a user the most of the functionalities of existing adaptive simplification algorithms in one place and is quite simple to implement. The proposed new underlying data structures are compact and support real time navigation across continuous LODs of a model; any desirable LOD can be extracted efficiently and can further be fine-tuned. The proposed model for adaptive simplification supports two key operations for selective refinement and selective simplification; their effect has been shown on various polygonal models. Comparison with related work shows that the proposed model provides combined environment at reduced overhead of memory space usage and faster running times.
用户控制的多边形模型简化
多边形模型在计算机图形学中无处不在,但由于其巨大的尺寸和复杂性,它们的实时操作和渲染,特别是在交互式应用环境中,已经成为一种威胁。在过去的十年里,出现了一系列的自动算法来帮助解决这个问题,但是它们统一地降低了模型的复杂性,而不关心网格局部部分的语义重要性。只有少数算法处理多边形模型的自适应简化。我们利用简化层次和超三角化模型提出了一种新的用户驱动简化模型[P]。Cignoni等人],在一个地方为用户提供了现有自适应简化算法的大部分功能,并且实现起来非常简单。提出的新底层数据结构紧凑,支持跨模型连续lod的实时导航;任何期望的LOD都可以有效地提取,并可以进一步微调。提出的自适应简化模型支持两个关键操作:选择性细化和选择性简化;它们的作用已在各种多边形模型上得到证明。与相关工作的比较表明,该模型在减少内存空间使用开销和加快运行时间的情况下提供了组合环境。
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