matlab: How to get textured using triangulation points in 3d reconstruction - matlab

I am working on 3d Reconstruction from two views. Till now I have got Fundamental matrix, Essential matrix and Triangulation Points. After this stage, how do I go forward to obtain textured image from the input image? and save those results in VRML model?

Are your cameras calibrated? If so, then you can rectify the images, and get a dense reconstruction. You can then plot the points using the colors from the RGB image. See this example.

Related

Volume reconstruction from 3D image gradient in Matlab

For 2D images- Gx and Gy gives the information on vertical and horizontal edge infromation respectively. Angle of the gradient direction vector can be calculated from inverse of tan(Gy/Gx) and edge direction will be perpendicular to the gradient direction vector.
I have 3D Z-stacked image datset so each pixel will be represented by (x,y,z) co-ordinate and with respective intensity value as well. I have used 3D image gradient link for initial reference.
(1) What if I want to derive whole volume/wireframe model just with the information of 3D image gradient magnitude and direction?
(2) Do I need X, Y and Z-stacked image data seperately in order to generate whole volume/wireframe model out of it?
In matlab, I can also develop whole volume just with 2D z-stacked masks using isosurface command. Here I am exploring other possibilities to generate wireframe volume/3D model.
Thanking you in anticipation.

How to apply 2D active contours (snakes) in 3D image?

I am trying to apply a snake method on a 3D image with no sucess. To my understanding, MATLAB's "activecontours" can be applied to 3D images but it seems that it fits a surface (balloon) into an object, instead of a single contour (snake). Or at least it seems to repeat the seed contour slice by slice, instead of fitting a single countour into a 3D object, because the end result is the whole 3D image segmented. I am looking for an active contour that has 3D awareness, as suggested by the following figure:
If the seed contour is the blue contour (slightly in perspective as to see it is a contour), I want the final snake to be the green one, as it fits the closest and easiest edge, instead of the red one, which would happen if I simply applied a 2D snake onto a slice of the 3D image coplanar with the seed contour. Thanks for your time!

How to plot two 2D histograms on the same 2D image?

I wonder if anyone can help me to plot two 2D histograms on the same plot.
I do some lifetime imaging and I want to reproduce my result as histograms (phasor plot method). I know how to plot a single 2D histogram, but not more, without removing the preceding one.
I am currently using the DIPimage toolbox, but I have seen that for plotting 2D histograms you can use as well the function 'ndhist'.
Please, find attached the picture. This is not obviously what I am after, as the background should be all blue and I would like to plot more 'clouds' over the universal circle.

plotting 3D edge in matlab

I have a 3D matrix of a MRI image and used matlab edge function and it gave me a 3D matrix as follow which some of the points are 1 (means edges).
I want to show this surface in matlab but I don't know that how I should do this. I know that I should use surf.
As #bdecaf said, you can use find to determine the height of the points, or in other words, in which of the 100 layers does the point lie. You can do that as follows:
z1=zeros(30,100);
temp=find(b);
[row,col,layer]=ind2sub(size(b),temp);
for i=1:size(x,1)
z1(row(i),col(i))=layer(i);
end
You can get an image as follows:

Multiview 3D reconstruction

I tried to do 3D reconstruction of multiple views by using multiview essential matrices to construct 3D view of each image view of object. However, I am shocked that the 3D points I found are all on about XY plane. I guess that it maybe regarding to the large value of essential matrix or weird number of projection matrix estimated. What are the suggestions for me to compute precise 3D points coordinate?
If you have the Computer Vision System Toolbox, this example may be helpful.