MATLAB 点云密度

算法思路是首先建立kd树,然后找到每个点距离最近的点的距离,对距离求和再求平均即可。

代码如下:

 1 clear all;
 2 close all;
 3 clc;
 4 
 5 pc = pcread('rabbit.pcd');
 6 pc = pcdownsample(pc,'random',0.1);   %降低一下数据量
 7 pc_point = pc.Location';                %得到点云数据
 8 kdtree = vl_kdtreebuild(pc_point);      %使用vlfeat建立kdtree
 9 
10 dissum = 0;
11 for i=1:length(pc_point)    
12     p_cur = pc_point(:,i);
13     [index, distance] = vl_kdtreequery(kdtree, pc_point, p_cur, 'NumNeighbors',2);    %寻找当前点最近的非自身点
14     dissum = dissum + sqrt(distance(2));        %距离求和
15 end
16 
17 avg = dissum / length(pc_point);
原文地址:https://www.cnblogs.com/ybqjymy/p/13645517.html