Finding matching points between two 2d point sets, but different sizes

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photoon
photoon el 25 de Feb. de 2021
Comentada: photoon el 26 de Feb. de 2021
I am trying to find the way of identifying matching points between two sets (they are xy coordinates from two shifted images). Their sizes are different. Both sets have many points that are not shared. In other words, I look for algoriths to find same points between two shifted 2D point sets, which are not identical.
  6 comentarios
photoon
photoon el 25 de Feb. de 2021
I am sorry. Let me attach them again.
There are no logic. I just chose them visually. If you scatter plot them, you will be able to tell easily.
photoon
photoon el 25 de Feb. de 2021
If we just use closest distance criteria, that wouldn't work because images from which points are collected are drifted from each other.

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Respuestas (3)

weikang zhao
weikang zhao el 25 de Feb. de 2021
if you dont need a very precise result,
clear
load('xy1.mat');
load('xy2.mat');
fixdistance=[-0.27,2.3];
newxy1=xy1+fixdistance;
dis=@(x,y) sum((x-y).^2);
result=struct([]);
structcount=1;
for i=1:size(newxy1,1)
for j=1:size(xy2,1)
if dis(xy2(j,:),newxy1(i,:))<0.1
result(structcount).xy1num=i;
result(structcount).xy2num=j;
result(structcount).xy1=xy1(i,:);
result(structcount).xy2=xy2(j,:);
structcount=structcount+1;
end
end
end
the struct result contains the results you need. If you need a more general and more accurate method to deal with a large number of similar problems, you need to design an algorithm to estimate fixdistance.
have fun!
  2 comentarios
weikang zhao
weikang zhao el 25 de Feb. de 2021
by the way, optical flow may be help to estimate fixdistance
photoon
photoon el 25 de Feb. de 2021
How to estimate fixdistance was my question. Thank you for your nice rephasement

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weikang zhao
weikang zhao el 26 de Feb. de 2021
I provide a feasible solution. Assuming that the length of xy1&`xy2` are m and n, first generate a set of size m*n, including the distance between any pair of points, and then deploy a clustering algorithm or GMM fitting algorithm, the cluster center is the fixdistance.

KSSV
KSSV el 26 de Feb. de 2021
Read about knnsearch.
  1 comentario
photoon
photoon el 26 de Feb. de 2021
I read knnsearch. Simply running knnsearch(xy1, xy2) gives a result. However, I don't thinkt this is what I want. Do I have a misunderstanding? Or could we apply this idea for measuring similiarity between two point sets?

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