3D reconstruction algorithm implementation is not working
I am trying to implement an algorithm to reconstruct 3D coordinates with known Z-component from 2D picture coordinates.
Using the Camera Calibration app of matlab, I calculated the intrinsic parameters. I used those and 4 points in the picture that I know the real world coordinates of to get extrinsic parameters.
I then used the method proposed In the original stack overflow post for 3d reconstruction:
After having all matrices, this equation that can help me with
transforming image point to wolrd coordinates:
where M is cameraMatrix, R - rotationMatrix, t - tvec, and s is an
unknown. Zconst represents the height where the orange ball is, in
this example it is 285 mm. So, first I need to solve previous
equation, to get "s", and after I can find out X and Y coordinate by
selecting image point:
%% Intrinsic camera parameters
cameraData = load("CameraParams.mat");
cameraParams = cameraData.cameraParams;
intrinsicMatrix = cameraParams.IntrinsicMatrix';
%% Points with known world coordinates
imagePoints = [224 92; 963 81; 200 653; 988 650];
worldPoints = [0 0; 114 0; 0 85; 114 85];
%% Points with unknown world xy-coordinates
unknownPoints = [416 280; 773 275; 414 479; 778 477];
zOffset = 0;
%% Extrinsic camera parameters
[rotationMatrix, translationVector] = extrinsics(imagePoints, worldPoints, cameraParams);
%% Transform image to world coordinates
results = zeros(length(unknownPoints), 3);
A = inv(intrinsicMatrix * rotationMatrix);
for i = 1:length(unknownPoints)
P = [unknownPoints(i,:) 1]';
AP = A * P;
At = A * translationVector';
s = (zOffset + At(3)) / AP(3);
results(i,:) = s * AP - At;
end
%% Visualization
allWorldPoints = [[worldPoints zeros(size(worldPoints, 1), 1)]; results];
allImagePoints = [imagePoints; unknownPoints];
[orientation, location] = extrinsicsToCameraPose(rotationMatrix, translationVector);
figure;
scatter(allImagePoints(:,1), allImagePoints(:,2));
figure;
plotCamera("Location", location, "Orientation", orientation, "Size", 20);
hold on;
pcshow(allWorldPoints, [0 0 0], "VerticalAxisDir", "down", "MarkerSize", 40);
The original picture looks like this (y-direction is flipped):
Whereas the reconstruction looks like this:
As you can see, the 4 fixed points used to compute the extrinsic parameters are displayed correctly but the reconstructed ones are in the wrong spots.
What is causing this error and how can I fix it?
matlab computer-vision projection 3d-reconstruction
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
add a comment |
I am trying to implement an algorithm to reconstruct 3D coordinates with known Z-component from 2D picture coordinates.
Using the Camera Calibration app of matlab, I calculated the intrinsic parameters. I used those and 4 points in the picture that I know the real world coordinates of to get extrinsic parameters.
I then used the method proposed In the original stack overflow post for 3d reconstruction:
After having all matrices, this equation that can help me with
transforming image point to wolrd coordinates:
where M is cameraMatrix, R - rotationMatrix, t - tvec, and s is an
unknown. Zconst represents the height where the orange ball is, in
this example it is 285 mm. So, first I need to solve previous
equation, to get "s", and after I can find out X and Y coordinate by
selecting image point:
%% Intrinsic camera parameters
cameraData = load("CameraParams.mat");
cameraParams = cameraData.cameraParams;
intrinsicMatrix = cameraParams.IntrinsicMatrix';
%% Points with known world coordinates
imagePoints = [224 92; 963 81; 200 653; 988 650];
worldPoints = [0 0; 114 0; 0 85; 114 85];
%% Points with unknown world xy-coordinates
unknownPoints = [416 280; 773 275; 414 479; 778 477];
zOffset = 0;
%% Extrinsic camera parameters
[rotationMatrix, translationVector] = extrinsics(imagePoints, worldPoints, cameraParams);
%% Transform image to world coordinates
results = zeros(length(unknownPoints), 3);
A = inv(intrinsicMatrix * rotationMatrix);
for i = 1:length(unknownPoints)
P = [unknownPoints(i,:) 1]';
AP = A * P;
At = A * translationVector';
s = (zOffset + At(3)) / AP(3);
results(i,:) = s * AP - At;
end
%% Visualization
allWorldPoints = [[worldPoints zeros(size(worldPoints, 1), 1)]; results];
allImagePoints = [imagePoints; unknownPoints];
[orientation, location] = extrinsicsToCameraPose(rotationMatrix, translationVector);
figure;
scatter(allImagePoints(:,1), allImagePoints(:,2));
figure;
plotCamera("Location", location, "Orientation", orientation, "Size", 20);
hold on;
pcshow(allWorldPoints, [0 0 0], "VerticalAxisDir", "down", "MarkerSize", 40);
The original picture looks like this (y-direction is flipped):
Whereas the reconstruction looks like this:
As you can see, the 4 fixed points used to compute the extrinsic parameters are displayed correctly but the reconstructed ones are in the wrong spots.
What is causing this error and how can I fix it?
matlab computer-vision projection 3d-reconstruction
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
add a comment |
I am trying to implement an algorithm to reconstruct 3D coordinates with known Z-component from 2D picture coordinates.
Using the Camera Calibration app of matlab, I calculated the intrinsic parameters. I used those and 4 points in the picture that I know the real world coordinates of to get extrinsic parameters.
I then used the method proposed In the original stack overflow post for 3d reconstruction:
After having all matrices, this equation that can help me with
transforming image point to wolrd coordinates:
where M is cameraMatrix, R - rotationMatrix, t - tvec, and s is an
unknown. Zconst represents the height where the orange ball is, in
this example it is 285 mm. So, first I need to solve previous
equation, to get "s", and after I can find out X and Y coordinate by
selecting image point:
%% Intrinsic camera parameters
cameraData = load("CameraParams.mat");
cameraParams = cameraData.cameraParams;
intrinsicMatrix = cameraParams.IntrinsicMatrix';
%% Points with known world coordinates
imagePoints = [224 92; 963 81; 200 653; 988 650];
worldPoints = [0 0; 114 0; 0 85; 114 85];
%% Points with unknown world xy-coordinates
unknownPoints = [416 280; 773 275; 414 479; 778 477];
zOffset = 0;
%% Extrinsic camera parameters
[rotationMatrix, translationVector] = extrinsics(imagePoints, worldPoints, cameraParams);
%% Transform image to world coordinates
results = zeros(length(unknownPoints), 3);
A = inv(intrinsicMatrix * rotationMatrix);
for i = 1:length(unknownPoints)
P = [unknownPoints(i,:) 1]';
AP = A * P;
At = A * translationVector';
s = (zOffset + At(3)) / AP(3);
results(i,:) = s * AP - At;
end
%% Visualization
allWorldPoints = [[worldPoints zeros(size(worldPoints, 1), 1)]; results];
allImagePoints = [imagePoints; unknownPoints];
[orientation, location] = extrinsicsToCameraPose(rotationMatrix, translationVector);
figure;
scatter(allImagePoints(:,1), allImagePoints(:,2));
figure;
plotCamera("Location", location, "Orientation", orientation, "Size", 20);
hold on;
pcshow(allWorldPoints, [0 0 0], "VerticalAxisDir", "down", "MarkerSize", 40);
The original picture looks like this (y-direction is flipped):
Whereas the reconstruction looks like this:
As you can see, the 4 fixed points used to compute the extrinsic parameters are displayed correctly but the reconstructed ones are in the wrong spots.
What is causing this error and how can I fix it?
matlab computer-vision projection 3d-reconstruction
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
I am trying to implement an algorithm to reconstruct 3D coordinates with known Z-component from 2D picture coordinates.
Using the Camera Calibration app of matlab, I calculated the intrinsic parameters. I used those and 4 points in the picture that I know the real world coordinates of to get extrinsic parameters.
I then used the method proposed In the original stack overflow post for 3d reconstruction:
After having all matrices, this equation that can help me with
transforming image point to wolrd coordinates:
where M is cameraMatrix, R - rotationMatrix, t - tvec, and s is an
unknown. Zconst represents the height where the orange ball is, in
this example it is 285 mm. So, first I need to solve previous
equation, to get "s", and after I can find out X and Y coordinate by
selecting image point:
%% Intrinsic camera parameters
cameraData = load("CameraParams.mat");
cameraParams = cameraData.cameraParams;
intrinsicMatrix = cameraParams.IntrinsicMatrix';
%% Points with known world coordinates
imagePoints = [224 92; 963 81; 200 653; 988 650];
worldPoints = [0 0; 114 0; 0 85; 114 85];
%% Points with unknown world xy-coordinates
unknownPoints = [416 280; 773 275; 414 479; 778 477];
zOffset = 0;
%% Extrinsic camera parameters
[rotationMatrix, translationVector] = extrinsics(imagePoints, worldPoints, cameraParams);
%% Transform image to world coordinates
results = zeros(length(unknownPoints), 3);
A = inv(intrinsicMatrix * rotationMatrix);
for i = 1:length(unknownPoints)
P = [unknownPoints(i,:) 1]';
AP = A * P;
At = A * translationVector';
s = (zOffset + At(3)) / AP(3);
results(i,:) = s * AP - At;
end
%% Visualization
allWorldPoints = [[worldPoints zeros(size(worldPoints, 1), 1)]; results];
allImagePoints = [imagePoints; unknownPoints];
[orientation, location] = extrinsicsToCameraPose(rotationMatrix, translationVector);
figure;
scatter(allImagePoints(:,1), allImagePoints(:,2));
figure;
plotCamera("Location", location, "Orientation", orientation, "Size", 20);
hold on;
pcshow(allWorldPoints, [0 0 0], "VerticalAxisDir", "down", "MarkerSize", 40);
The original picture looks like this (y-direction is flipped):
Whereas the reconstruction looks like this:
As you can see, the 4 fixed points used to compute the extrinsic parameters are displayed correctly but the reconstructed ones are in the wrong spots.
What is causing this error and how can I fix it?
matlab computer-vision projection 3d-reconstruction
matlab computer-vision projection 3d-reconstruction
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
edited Nov 18 '18 at 9:26
RobinW
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
asked Nov 17 '18 at 12:42
RobinWRobinW
7111
7111
add a comment |
add a comment |
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