基于八叉树的大规模流程工厂模型细节裁剪算法  

Improved small feature culling for large scale process plant model based on octree

作　　者：杜振林[1,2] 唐卫清[1,2,3] 覃力[1,2] 李士才 

机构地区：[1]中国科学院计算技术研究所,北京100190 [2]中国科学院大学计算机与控制学院,北京101408 [3]北京中科辅龙计算机技术股份有限公司,北京100085

出　　处：《计算机应用》2017年第9期2626-2630,共5页journal of Computer Applications

摘　　要：针对传统的细节裁剪算法,处理粒度为面片级,无法在规定时间内快速处理顶点、面片规模数以亿计的流程工厂模型的问题,提出一种基于八叉树的大规模流程工厂模型细节裁剪算法,用于解决传统细节裁剪效率低下的问题,以保证较高的交互帧率。该方法依据组成流程工厂模型的构件体素特征以及空间特征,提出用于量化构件大小的占屏值,并结合建立的八叉场景树,依据所述占屏值近似估算一系列构件投影至屏幕所占据的像素点数量上限,从而快速判断是否裁剪。实验结果表明,所提算法简单有效,与现今主流的漫游软件在加载具有10 000根管线的工厂模型后进行对比,其帧率至少提升50%,显著提升了平台的交互流畅度,对流程工厂行业以及图形平台整体的设计水平的提升有积极的意义。To eliminate the drawbacks of traditional small feature culling algorithm which processing granularity are triangles and can＇t efficiently cope with the number of vertexes and triangles up to hundreds of millions in a certain time period, an improved small feature culling algorithm for large scale process plant based on octree was proposed. Based on the component primitive characteristics and spatial characteristics of the process plant model, the value of screen for quantizing the size of component was proposed, and the established octree and the value of screen were combined to estimate the upper limit of the number of pixels, so as to quickly determine whether the component would be culled or not. The experimental results show that the proposed algorithm is simple and effective. Compared with the current popular review software after loading the factory model with 10000 pipelines, the frame rate is increased by at least 50%, which greatly improves the platform＇s fluency. Process factory industry and graphics platform as a whole to enhance the level of design has a positive meaning.

关 键 词：流程工厂模型 细节裁剪 八叉树 体素特征 帧率 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]