使用KD树搜索的维数少于云 [英] Use a KD Tree to search in fewer dimensions than the cloud

问题描述

我想使用2D(xy)标准在3D(xyz)中搜索点云.

I'd like to search my 3D (xyz) for point cloud using a 2D (xy) criteria.

即找到x = 2 AND y = 4附近的所有点，无论其Z坐标如何"

i.e. "Find all the points near x=2 AND y=4 regardless of their Z coordinate"

从概念上讲，我认为我可以通过创建仅考虑x&的KD树来解决此问题.是的，但是我似乎还是找不到PCL工具来做到这一点.

Conceptually, I thought I could solve this by creating a KD tree that only considered x & y, but I can't seem to find anyway with the PCL tools to do that.

是否有一个好的(已经写好的)方法来做到这一点?还是我必须实现自己的[可能较慢的] Kd树?

Is there a good (already written) way to do this? Or will I have to implement my own [likely slower] Kd tree?

推荐答案

如果您正在考虑KD树，那么对检索到的点有一些限制，无论是最近点数还是它们的距离.

If you were thinking about a KD Tree, then you are having some limits on the retrieved points either by number of closest or their distance.

在您的情况下，那应该是距离，所以，您就得到了(x-dx, x+dx) and (y-dy, y+dy)之间的点.

In your case, that should be the distance, So, then you get the point between (x-dx, x+dx) and (y-dy, y+dy).

在pcl中执行此操作的一种方法是使用 pcl :: getPointsInBox()

One way to do that in pcl is using pcl::getPointsInBox()

在给定边界的情况下获取位于框中的一组点.

Get a set of points residing in a box given its bounds.

参数

cloud the point cloud data message
min_pt    the minimum bounds
max_pt    the maximum bounds
indices   the resultant set of point indices residing in the box

因此，如果要获得x(1.25，1.75)和y(2.25，2.75)之间的点，则必须创建两个MinMax点，如下所示:

So, if you want to get points between x(1.25, 1.75) and y(2.25, 2.75), you have to create the two MinMax points as follows :

PointMin(1.25, 2.25, min_z)
PointMax(1.75, 2.75, max_z)

min_z & max_z可以任意设置为高和低(-15，40)，这意味着您将获得具有指定(x，y)范围的所有点，而无需考虑(z)

min_z & max_z could be set arbitrarly low and high as(-15, 40), granting that you'll be getting all the points with the specified (x,y) range without regard to (z)

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