摘要
随着城市规模和场景复杂度的不断提高,虚拟地理环境下实现大规模三维场景高逼真的实时渲染是数字城市可视化平台的瓶颈之一。通常利用区域的可见性计算来剔除三维空间数据中被遮挡而导致不可见的对象,从而提高大规模三维场景的渲染效率。针对传统区域可见性计算空间划分粒度细的问题,提出了一种自适应性空间网格划分计算潜在可见集(potentially visible set,PVS)的方法。首先构建场景区域的AABB(axis-aligned bounding box)包围盒,在水平方向上对该包围盒进行四叉树划分,在垂直方向上对该包围盒进行层次划分得到相应的空间场景单元,通过光线投射计算出空间场景单元的潜在可见集。实验结果表明,通过本文方法来计算场景单元的潜在可见集,可以大幅度提高遮挡剔除率。当相机进入某个空间场景单元后,只绘制当前场景单元的可见对象,对不可见的对象不进行绘制,从而提高实时渲染的帧率。
With the constant increase in the city scale and complexity of scenes in recent years,realizing real-time rendering of large-scale 3D scenes with high fidelity in a virtual geographic environment is one of the bottlenecks of the digital city visualization platform.Usually,the visibility calculation of the region is used to eliminate the invisible objects in the 3D spatial data,so as to improve the rendering efficiency of 3D urban scenes.In view of the problem like fine granularity of region division in traditional region visibility calculation,an adaptive spatial partition method to calculate the potentially visible sets of urban scenes is proposed in this paper.Firstly,the axis-aligned bounding box of urban 3D scene is constructed,and then the axis-aligned bounding box is divided by quadtree in the horizontal direction and hierarchy in the vertical direction.Finally,the potential visible sets of spatial scene cell is calculated by ray casting.The experimental results show that this method can greatly improve the occlusion rejection rate by calculating the potential visible set of scene units.When the camera enters a scene unit,only the visible objects of the current scene unit are drawn,and the invisible objects are not drawn,so as to improve the frame rate of realtime rendering.
作者
徐海
贺彪
张琛
林浩嘉
李泽宇
XU Hai;HE Biao;ZHANG Chen;LIN Haojia;LI Zeyu(Research Institute for Smart Cities,School of Architecture and Urban Planning,Shenzhen 518060,China;Shenzhen Key Laboratory of Digital Twin Technologies for Cities,Shenzhen 518060,China;School of Resources and Environmental Sciences,Wuhan University,Wuhan 430079,China;School of City and Environment,Hubei Normal University,Huangshi 435002,China)
出处
《测绘地理信息》
CSCD
2023年第2期80-85,共6页
Journal of Geomatics
基金
国家重点研发计划(2019YFB2103104)
鹏城国家实验室科研项目(PCNL2021ZDXM07)。
