Question

I have a huge 3D pointcloud, [3x40e6]. It’s a pointcloud of a flat surface, so it’s more like 2.5D in that sense. I would like to bin the pointcloud into a fixed mesh range so that i can just put it into a 2D matrix and view it with imagesc(mymap).

I did solve this problem, but it takes too long. This is what i got so far. It works fine but takes 10 minutes. It interpolates all kind of jive and i don’t need that.

xlin=linspace(min(xx),max(xx),meshsz*dxxyy);
ylin=linspace(min(yy),max(yy),meshsz);
[X,Y]=meshgrid(xlin,ylin);
disp('+ Flattening (X,Y,Z) information into 2D (X,Y)(Z) mesh..')
%Fit to 2D grid (takes a long time)
Z=griddata(xx,yy,zz,X,Y);%,'cubic');

What i would really want to do is bin all the data from my [3xN] vector into my specific 2D range map. I guess i would have to bin all the values into that map (there are some excellent and fast binning algorithms) but i would also need the specific Z-coordinate scalars in there because that’s what i want to average in each bin.

Thanks!

Answer 1

Solved. Takes 200ms per million points.

yidx=[min(yy):dy:max(yy)];
xidx=[min(xx):dx:max(xx)];
ZmapSum=zeros(length(yidx),length(xidx));
ZmapIdx=zeros(size(ZmapSum));

[nx,binx] = histc(xx,xidx);
[ny,biny] = histc(yy,yidx);
%bin==0 means the value is out of range
binx=binx+1; biny=biny+1;
%binzero=( (binx==0) | (biny==0) );
%binx(binzero) = [];
%biny(binzero) = [];
%xx(binzero) = [];
%yy(binzero) = [];
%zz(binzero) = [];

%binx and biny give their respective bin locations
for i=1:1:length(xx)
    ZmapSum(biny(i),binx(i))=ZmapSum(biny(i),binx(i))+zz(i);
    ZmapIdx(biny(i),binx(i))=ZmapIdx(biny(i),binx(i))+1;
end

Zmap=ZmapSum./ZmapIdx;