36 lines
900 B
Mathematica
36 lines
900 B
Mathematica
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function [ptsOut,indexSet] = reducePts_haa(pts, dst)
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%Reduces a point set, pts, in a stochastic manner, such that the minimum sdistance
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% between points is 'dst'. Writen by abd, edited by haa, then by raje
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nPoints=size(pts,2);
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indexSet=true(nPoints,1);
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RandOrd=randperm(nPoints);
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%tic
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NS = KDTreeSearcher(pts');
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%toc
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% search the KNTree for close neighbours in a chunk-wise fashion to save memory if point cloud is really big
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Chunks=1:min(4e6,nPoints-1):nPoints;
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Chunks(end)=nPoints;
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for cChunk=1:(length(Chunks)-1)
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Range=Chunks(cChunk):Chunks(cChunk+1);
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idx = rangesearch(NS,pts(:,RandOrd(Range))',dst);
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for i = 1:size(idx,1)
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id =RandOrd(i-1+Chunks(cChunk));
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if (indexSet(id))
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indexSet(idx{i}) = 0;
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indexSet(id) = 1;
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end
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end
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end
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ptsOut = pts(:,indexSet);
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disp(['downsample factor: ' num2str(nPoints/sum(indexSet))]);
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