Reputation: 1254
I'm trying to implement the normalized 8-point algorithm to estimate the fundamental matrix. One step is to normalize the points such that they have center (0,0)
and mean distance of sqrt(2)
. I know how to translate and scale the points to do so, but how do I represent the steps as a matrix to use at a later step?
My current function transforms the points as below, but I also need to figure out what the transformation matrix is:
%% Normalize points to have center (0,0) and mean distance sqrt(2)
function [pts1, T] = normalizePoints(pts)
Xs = pts(:,1);
Ys = pts(:,2);
%% Compute old center and translate
Xc = mean(Xs);
Yc = mean(Ys);
Xs = Xs - Xc;
Ys = Ys - Yc;
%% Compute mean distance and scale
Ds = sqrt(Xs .^ 2 + Ys .^ 2);
meanD = mean(Ds);
scale = sqrt(2) / meanD;
pts1 = [Xs .* scale, Ys .* scale];
T = ... % How do I represent the previous operations as T?
end
Upvotes: 0
Views: 299
Reputation: 4195
T = [3;5];
% Normalize points to have center (0,0) and mean distance sqrt(2)
pts = rand(10,2);
Xs = pts(:,1);
Ys = pts(:,2);
% Compute old center and translate
Xc = mean(Xs);
Yc = mean(Ys);
Xs = Xs - Xc;
Ys = Ys - Yc;
% Compute mean distance and scale
Ds = sqrt(Xs .^ 2 + Ys .^ 2);
meanD = mean(Ds);
scale = sqrt(2) / meanD;
% composing transformation matrix
H = eye(3);
H([1,5]) = H([1,5])*scale;
H(1:2,3) = T(:);
% making homogenous coordinates (add ones as z values)
ptsHomo = [pts';ones(1,size(pts,1))];
% apply transform
ptsRes = H*ptsHomo;
ptsRes = bsxfun(@rdivide,ptsRes(1:2,:),ptsRes(3,:))';
subplot(121);
plot(pts(:,1),pts(:,2),'o');
title('original points')
subplot(122);
plot(ptsRes(:,1),ptsRes(:,2),'o');
title('transformed points')
Upvotes: 1