The space partitioning algorithm based on the rounding and addressing operations has been proved to be an efficient space partitioning algorithm with the potential for real-time calculation.An improvement on this kind...The space partitioning algorithm based on the rounding and addressing operations has been proved to be an efficient space partitioning algorithm with the potential for real-time calculation.An improvement on this kind of space partitioning algorithms for solving complex 3D models is presented.Numerical examples show that the efficiency of the improved algorithm is better than that of the original method.When the size of most target elements is smaller than the size of spatial grids,the efficiency of the improved method can be more than four times of that of the original method.An adaptive method of space partitioning based on the improved algorithm is developed by taking the surface element density or the curvature as the threshold for deep partitioning and conducting the deep partitioning using the octree method.A computer program implementation for applying the method in some typical applications is discussed,and the performance in terms of the efficiency,reliability,and resource use is evaluated.Application testing shows that the results of the adaptive spacing partitioning are more convenient for the follow-up use than that of the basic uniform space partitioning.Furthermore,when it is used to calculate the electromagnetic scattering of complex targets by the ray tracing(RT)method,the adaptive space partitioning algorithm can reduce the calculation time of the RT process by more than 40%compared with the uniform space segmentation algorithm.展开更多
针对三角面元目标提出了一种高效率的空间分割算法.该方法以一种空间点与单位立方体位置关系的判断法则为基础,并逐渐延拓到参数直线、三角形的空间分割上,给出了一种新的三角形面元目标快速分割的解决方法.介绍了该方法在参数曲线、NUR...针对三角面元目标提出了一种高效率的空间分割算法.该方法以一种空间点与单位立方体位置关系的判断法则为基础,并逐渐延拓到参数直线、三角形的空间分割上,给出了一种新的三角形面元目标快速分割的解决方法.介绍了该方法在参数曲线、NURBS(Non-Uniform Rational B-Spline)曲面目标的空间均匀分割上的应用,并给出了非均匀分割的处理方法.与计算机图形技术中最常用的BSP(Binary Space Partitioning)技术的比较中发现,对于特定情形,该算法的执行效率优于BSP法.通过实例证明了该算法的有效性和可靠性.展开更多
Regularized Boolean operations have been widely used in 3D modeling systems. However, evaluating Boolean operations may be quite numerically unstable and time consuming, especially for iterated set operations. A novel...Regularized Boolean operations have been widely used in 3D modeling systems. However, evaluating Boolean operations may be quite numerically unstable and time consuming, especially for iterated set operations. A novel and unified technique is proposed in this paper for computing single and iterated set operations efficiently, robustly and exactly. An adaptive octree is combined with a nested constructive solid geometry （CSG） tree by this technique. The intersection handling is restricted to the cells in the octree where intersection actually occurs. Within those cells, a CSG tree template is instanced by the surfaces and the tree is converted to planebased binary space partitioning （BSP） for set evaluation; Moreover, the surface classification is restricted to the ceils in the octree where the surfaces only come from a model and are within the bounding-boxes of other polyhedrons. These two ways bring about the efficiency and scalability of the operations, in terms of runtime and memory. As all surfaces in such a cell have the same classification relation, they are classified as a whole. Robustness and exactness are achieved by integrating plane-based geometry representation with adaptive geometry predicate technique in intersection handling, and by applying divide-and-conquer arithmetic on surface classification. Experimental results demonstrate that the proposed approach can guarantee the robustness of Boolean computations and runs faster than other existing approaches.展开更多
基金This work was supported by the National Natural Science Foundation of China(61601015,91538204).
文摘The space partitioning algorithm based on the rounding and addressing operations has been proved to be an efficient space partitioning algorithm with the potential for real-time calculation.An improvement on this kind of space partitioning algorithms for solving complex 3D models is presented.Numerical examples show that the efficiency of the improved algorithm is better than that of the original method.When the size of most target elements is smaller than the size of spatial grids,the efficiency of the improved method can be more than four times of that of the original method.An adaptive method of space partitioning based on the improved algorithm is developed by taking the surface element density or the curvature as the threshold for deep partitioning and conducting the deep partitioning using the octree method.A computer program implementation for applying the method in some typical applications is discussed,and the performance in terms of the efficiency,reliability,and resource use is evaluated.Application testing shows that the results of the adaptive spacing partitioning are more convenient for the follow-up use than that of the basic uniform space partitioning.Furthermore,when it is used to calculate the electromagnetic scattering of complex targets by the ray tracing(RT)method,the adaptive space partitioning algorithm can reduce the calculation time of the RT process by more than 40%compared with the uniform space segmentation algorithm.
文摘针对三角面元目标提出了一种高效率的空间分割算法.该方法以一种空间点与单位立方体位置关系的判断法则为基础,并逐渐延拓到参数直线、三角形的空间分割上,给出了一种新的三角形面元目标快速分割的解决方法.介绍了该方法在参数曲线、NURBS(Non-Uniform Rational B-Spline)曲面目标的空间均匀分割上的应用,并给出了非均匀分割的处理方法.与计算机图形技术中最常用的BSP(Binary Space Partitioning)技术的比较中发现,对于特定情形,该算法的执行效率优于BSP法.通过实例证明了该算法的有效性和可靠性.
基金supported by the Natural Science Foundation of China under Grant No.61202154 and No.61133009the National Basic Research Project of China under Grant No.2011CB302203+2 种基金Shanghai Pujiang Program under Grant No.13PJ1404500the Science and Technology Commission of Shanghai Municipality Program under Grant No.13511505000the Open Project Program of the State Key Lab of CAD&CG of Zhejiang University under Grant No.A1401
文摘Regularized Boolean operations have been widely used in 3D modeling systems. However, evaluating Boolean operations may be quite numerically unstable and time consuming, especially for iterated set operations. A novel and unified technique is proposed in this paper for computing single and iterated set operations efficiently, robustly and exactly. An adaptive octree is combined with a nested constructive solid geometry （CSG） tree by this technique. The intersection handling is restricted to the cells in the octree where intersection actually occurs. Within those cells, a CSG tree template is instanced by the surfaces and the tree is converted to planebased binary space partitioning （BSP） for set evaluation; Moreover, the surface classification is restricted to the ceils in the octree where the surfaces only come from a model and are within the bounding-boxes of other polyhedrons. These two ways bring about the efficiency and scalability of the operations, in terms of runtime and memory. As all surfaces in such a cell have the same classification relation, they are classified as a whole. Robustness and exactness are achieved by integrating plane-based geometry representation with adaptive geometry predicate technique in intersection handling, and by applying divide-and-conquer arithmetic on surface classification. Experimental results demonstrate that the proposed approach can guarantee the robustness of Boolean computations and runs faster than other existing approaches.
