【PCL】octree

https://blog.csdn.net/qq_36686437/article/details/114160640?spm=1001.2101.3001.6650.6&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-6-114160640-blog-123367811.pc_relevant_aa&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-6-114160640-blog-123367811.pc_relevant_aa&utm_relevant_index=12

https://blog.csdn.net/me1171115772/article/details/105839239

https://blog.csdn.net/weixin_43928944/article/details/116153120

https://blog.csdn.net/suyunzzz/article/details/98785640

https://blog.csdn.net/HUASHUDEYANJING/article/details/123367811

https://blog.csdn.net/daidaiisdaidai/article/details/84699222

https://blog.csdn.net/weixin_41966507/article/details/123028763?spm=1001.2101.3001.6650.5&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-5-123028763-blog-116153120.pcrelevantt0_20220926_downloadratepraise_v1&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-5-123028763-blog-116153120.pcrelevantt0_20220926_downloadratepraise_v1&utm_relevant_index=6

https://blog.csdn.net/timzc/article/details/6060591?spm=1001.2101.3001.6650.18&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-18-6060591-blog-123028763.pc_relevant_multi_platform_whitelistv6&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-18-6060591-blog-123028763.pc_relevant_multi_platform_whitelistv6&utm_relevant_index=23

https://blog.csdn.net/wdf666520/article/details/110491507

https://blog.csdn.net/qq_37855507/article/details/90957798?spm=1001.2101.3001.6650.6&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-6-90957798-blog-123028763.pc_relevant_multi_platform_whitelistv6&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-6-90957798-blog-123028763.pc_relevant_multi_platform_whitelistv6&utm_relevant_index=11

https://hermit.blog.csdn.net/article/details/112851934?spm=1001.2101.3001.6650.13&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-13-112851934-blog-123028763.pc_relevant_multi_platform_whitelistv6&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-13-112851934-blog-123028763.pc_relevant_multi_platform_whitelistv6&utm_relevant_index=18

https://blog.csdn.net/qq_30815237/article/details/86509233

https://blog.csdn.net/Augusdi/article/details/36001543?spm=1001.2101.3001.6650.7&utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-7-36001543-blog-123028763.pc_relevant_multi_platform_whitelistv6&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EBlogCommendFromBaidu%7ERate-7-36001543-blog-123028763.pc_relevant_multi_platform_whitelistv6&utm_relevant_index=12

 

 

 

1.octree简介
octree是一中用于描述三位空间的树状数据结构。octree的每个节点表示一个正方体的体积元素,每个节点有八个子节点,将八个子节点所表示的体积元素加在一起就等于父节点的体积。octree是四叉树在三维空间上的扩展,二维上我们有四个象限,而三维上,我们有8个卦限。octree主要用于空间划分和最近邻搜索。
2.octree实现原理
(1). 设定最大递归深度
(2). 找出场景的最大尺寸,并以此尺寸建立第一个立方体
(3). 依序将单位元元素丢入能被包含且没有子节点的立方体
(4). 若没有达到最大递归深度,就进行细分八等份,再将该立方体所装的单位元元素全部分担给八个子立方体
(5). 若发现子立方体所分配到的单位元元素数量不为零且跟父立方体是一样的,则该子立方体停止细分,因为跟据空间分割理论,细分的空间所得到的分配必定较少,若是一样数目,则再怎么切数目还是一样,会造成无穷切割的情形。
(6). 重复3,直到达到最大递归深度。

posted @ 2022-09-27 12:00  星火-AI  阅读(43)  评论(0编辑  收藏  举报