pc_point= pc.Location'; %得到点云数据kdtree =vl_kdtreebuild(pc_point); %使用vlfeat建立kdtree dissum=0;fori=1:length(pc_point) p_cur=pc_point(:,i); [index, distance]= vl_kdtreequery(kdtree, pc_point, p_cur,'NumNeighbors',2); %寻找当前点最近的非自身点 dissum= dissum + sq...
'random',0.1); %降低一下数据量7pc_point = pc.Location'; %得到点云数据8kdtree = vl_kdtreebuild(pc_point); %使用vlfeat建立kdtree910dissum =0;11fori=1:length(pc_point)12p_cur =pc_point(:,i);13[index, distance] = vl_kdtreequery(kdtree, pc_point, p_cur,'NumNeighbors',2); ...
'random',0.1); %降低一下数据量7pc_point = pc.Location'; %得到点云数据8kdtree = vl_kdtreebuild(pc_point); %使用vlfeat建立kdtree910dissum =0;11fori=1:length(pc_point)12p_cur =pc_point(:,i);13[index, distance] = vl_kdtreequery(kdtree, pc_point, p_cur,'NumNeighbors',2); ...
下面是一个使用VLFeat求K近邻的一个例子 clc,clear X = rand(2,100);%一百个二维列向量 kdtree = vl_kdtreebuild(X);%构建kd树 Q = rand(2,1); [index,distance] = vl_kdtreequery(kdtree, X, Q);%返回X中与Q最近的点 [index, distance] = vl_kdtreequery(kdtree, X, Q, 'NumNeighbors'...
pc_point= pc.Location'; %得到点云数据kdtree =vl_kdtreebuild(pc_point); %使用vlfeat建立kdtree normE=[];fori=1:length(pc_point) p_cur=pc_point(:,i); [index, distance]= vl_kdtreequery(kdtree, pc_point, p_cur,'NumNeighbors',10); %寻找当前点最近的10个点 ...
kdtree = vl_kdtreebuild(X); % 计算Q的k个近邻 [index, distance] = vl_kdtreequery(kdtree, X, Q, 'NumNeighbors', 5) ; 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. KNN原理介绍: 二、邻接矩阵A的构建 1.邻接矩阵A 采用如下的公式来构造链接矩阵A,其中N ...
vl_kdtreequery) - Spatial histograms (vl_binsum, vl_binsearch) • Learning and classification - Fast linear SVMs - PEGASOS (vl_pegasos) - Fast non-linear SVMs - Homogeneous kernel maps (vl_homkermap) • Other VLFeat features • The VLFeat library- SIFT example (vl_sift)• Caltech...