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function v_noisy = addNoise(v_clean,focal_length,pixel_noise)
%find good vector in normal plane based on good conditioning
inPlaneVector1 = zeros(3,1);
if v_clean(1,1) > v_clean(2,1) && v_clean(1,1) > v_clean(3,1)
inPlaneVector1(2,1) = 1.0;
inPlaneVector1(3,1) = 0.0;
inPlaneVector1(1,1) = 1.0/v_clean(1,1) * (-v_clean(2,1));
else
if v_clean(2,1) > v_clean(3,1) && v_clean(2,1) > v_clean(1,1)
inPlaneVector1(3,1) = 1.0;
inPlaneVector1(1,1) = 0.0;
inPlaneVector1(2,1) = 1.0/v_clean(2,1) * (-v_clean(3,1));
else
%v_clean(3,1) > v_clean(1,1) && v_clean(3,1) > v_clean(2,1)
inPlaneVector1(1,1) = 1.0;
inPlaneVector1(2,1) = 0.0;
inPlaneVector1(3,1) = 1.0/v_clean(3,1) * (-v_clean(1,1));
end
end
%normalize the in-plane vector
inPlaneVector1 = inPlaneVector1 / norm(inPlaneVector1);
inPlaneVector2 = cross(v_clean,inPlaneVector1);
noiseX = pixel_noise * (rand-0.5)*2.0;% / sqrt(2);
noiseY = pixel_noise * (rand-0.5)*2.0;% / sqrt(2);
v_noisy = focal_length * v_clean + noiseX * inPlaneVector1 + noiseY * inPlaneVector2;
v_noisy_norm = norm(v_noisy);
v_noisy = v_noisy ./ v_noisy_norm;
end
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