摘要
大体量3D模型容易导致浏览器端渲染帧数低、显示卡顿及资源消耗大等问题,其原因是这类模型通常包含数以亿计的三角面片,在有限的时间内无法实现快速加载与渲染。针对此类问题,提出一种基于优化八叉树的场景视锥体裁剪算法。该算法采用地址码(Morton码)、节点视距标准和按需增量划分技术,使得八叉树具有自适应性与良好的压缩效率;采用双层包围体和基础相交测试技术,提高视锥体裁剪的精确性,整体上实现提升渲染帧数、显示流畅的目标。高速列车实例模型研究表明,与传统八叉树视锥体裁剪算法相比,所提算法平均渲染帧数上提高了约14帧,空间压缩率提高了37.8个百分点。
Large-volume 3D models are prone to low rendering frame rate,slow display and large resource consumption on the browser side.The reason is that such models usually contain hundreds of millions of triangular slices,which cannot be loaded and rendered quickly in a limited time.To address such problems,a scene view frustum culling algorithm based on an optimized octree is proposed.The algorithm adopts address code(Morton code),node view distance criterion and on-demand incremental division technique,which makes the octree adaptive with good compression efficiency;it adopts double bounding volume and base intersection test techniques to improve the accuracy of view frustum culling and achieves the overall goal of improving ren dering frame rate and smooth display.The high-speed train example model study shows that the proposed algorithm improves the average rendering frame rate by about 14 frames and the spatial compression rate by about 37.8 percentage points compared with the traditional octree view frustum culling algorithm.
作者
李颖颖
黄文培
LI Ying-ying;HUANG Wen-pei(College of Computers and Artificial Intelligence,Southwest Jiaotong University,Chengdu 611756,China;College of Information Science and Technology,Southwest Jiaotong University,Chengdu 611756,China)
出处
《计算机与现代化》
2024年第1期103-108,共6页
Computer and Modernization
基金
国家重点研发计划项目(2020YFB1708000)
四川省重点研发计划项目(2021YFG0039)。
关键词
地址码
视距标准
按需增量划分
自适应性
双层包围体
基础相交测试
Morton code
view distance criteria
on-demand increments division
adaptivity
double bounding volume
base in tersection test
