projection

I am trying to use MATLAB to implement a CT (computed tomography) projection operator, A, which I think is also referred as "system matrix" often times. Basically, for a N x N image M, the projection data, P, can be obtained by multiplication of the project operator to the image: P = AM and the backprojection procedure can be performed by multiplying the (conjugate) transpose of the projection operator to the projection data: M = A'P Anyone has any idea/example/sample code on how to implement matrix A (for example: Radon transform)? I would really like to start with a small size of matrix, say

I'm trying to write a projection function that could transform a vector<T> into a vector<R> . Here is an example: auto v = std::vector<int> {1, 2, 3, 4}; auto r1 = select(v, [](int e){return e*e; }); // {1, 4, 9, 16} auto r2 = select(v, [](int e){return std::to_string(e); }); // {"1", "2", "3", "4"} First attempt: template<typename T, typename R> std::vector<R> select(std::vector<T> const & c, std::function<R(T)> s) { std::vector<R> v; std::transform(std::begin(c), std::end(c), std::back_inserter(v), s); return v; } But for auto r1 = select(v, [](int e){return e*e; }); I get: error C2660:

I wish to determine the 2D screen coordinates (x,y) of points in 3D space (x,y,z). The points I wish to project are real-world points represented by GPS coordinates and elevation above sea level. For example: Point (Lat:49.291882, Long:-123.131676, Height: 14m) The camera position and height can also be determined as a x,y,z point. I also have the heading of the camera (compass degrees), its degree of tilt (above/below horizon) and the roll (around the z axis). I have no experience of 3D programming, therefore, I have read around the subject of perspective projection and learnt that it

Given: A 3D mesh defined with a set of vertices and triangles building up the mesh with these points. Problem: Find the 2d outline of the projected arbitrarily rotated mesh on an arbitrary plane. The projection is easy. The challenge lies in finding the "hull" of the projected triangle edges in the plane. I need some help with input/pointers on researching this algorithm. For simplicity, we can assume the 3D edges are projected straight down onto the xy plane. Start with the rightmost point (the point with the biggest x coordinate) Get all edges from this point Follow the edge with the

Ptoject Tango provides a point cloud, how can you get the position in pixels of a 3D point in the point cloud in meters? I tried using the projection matrix but I get very small values (0.5,1.3 etc) instead of say 1234,324 (in pixels). I include the code I have tried //Get the current rotation matrix Matrix4 projMatrix = mRenderer.getCurrentCamera().getProjectionMatrix(); //Get all the points in the pointcloud and store them as 3D points FloatBuffer pointsBuffer = mPointCloudManager.updateAndGetLatestPointCloudRenderBuffer().floatBuffer; Vector3[] points3D = new Vector3[pointsBuffer.capacity()

I have a binary which has some text on different parts of the image like at the bottom, top, center, right middle center, etc. Original Image The areas I would like to focus on are the manually drawn regions shown in red. I calculated the horizontal and vertical summations of the image and plotted them: plot(sum(edgedImage1,1)) plot(sum(edgedImage1,2)) Can somebody give me explanation of what these plots are telling me about the original image with regards to the structure of which I explained above? Moreover, how could these plots help me extracting those regions I just manually drew in red?