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Orbisnap asked . 2021-08-13

Simulink 3D Animation: how to compute the projection matrix

Simulink 3D Animation: how to compute the projection matrix associated with the camera view in a virtual reality world?

I am using Simulink 3D Animation to model a virtual reality environment.
 
In MATLAB, how do I calculate the projection of the world in the same way as it is rendered on the screen?

sl3d , simulink , 3d animation , camera , projection , matrix

Expert Answer

Neeta Dsouza answered . 2025-03-27 16:14:13

In Simulink 3D Animation, the projection matrix of a camera determines how a 3D scene is projected onto a 2D plane. To compute the projection matrix for a camera view in a virtual reality world, you can use the following steps in MATLAB.

Steps to Compute the Projection Matrix:

  1. Access the Camera Node:

    • Load the virtual reality world using vrworld.
    • Access the specific camera node using getfield or directly accessing the camera properties.
  2. Extract Camera Parameters:

    • Retrieve the camera's intrinsic parameters (field of view, aspect ratio, etc.).
    • Get the extrinsic parameters (position and orientation of the camera).
  3. Build the Projection Matrix:

    • Combine the intrinsic and extrinsic parameters to construct the projection matrix.
    • The projection matrix PP maps a 3D point X\mathbf{X} in world coordinates to a 2D point x\mathbf{x} on the image plane: x=PX\mathbf{x} = P \mathbf{X}

Example Code to Compute the Projection Matrix:

 

% Load the virtual reality world
vr_world = vrworld('my_vr_world.wrl');
open(vr_world);

% Access the camera node
camera_node = vrnode(vr_world, 'CameraNodeName'); % Replace with the actual camera node name

% Retrieve camera parameters
field_of_view = camera_node.fieldOfView; % Horizontal field of view in radians
aspect_ratio = camera_node.aspectRatio;  % Aspect ratio (width/height)
position = camera_node.translation;     % Camera position [x, y, z]
orientation = camera_node.rotation;     % Camera orientation [axis_x, axis_y, axis_z, angle]

% Compute intrinsic matrix (K)
f = 1 / tan(field_of_view / 2); % Focal length (assumes normalized coordinates)
K = [f / aspect_ratio, 0, 0;
     0, f, 0;
     0, 0, 1];

% Compute extrinsic matrix (R and t)
R = vrrotvec2mat(orientation); % Rotation matrix from orientation
t = -R * position';            % Translation vector
Rt = [R, t];                   % Combine rotation and translation

% Combine intrinsic and extrinsic to get the projection matrix
P = K * [R, t];

% Display the result
disp('Projection Matrix:');
disp(P);

Explanation of Parameters:

  1. Intrinsic Parameters:

    • field_of_view: Determines the horizontal field of view in radians.
    • aspect_ratio: Used to adjust the focal length for the height of the image.
  2. Extrinsic Parameters:

    • position: Camera position in the world coordinates.
    • orientation: A rotation vector (axis-angle format) representing the camera's orientation.
  3. Projection Matrix:

    • The projection matrix PP combines intrinsic (camera-specific) and extrinsic (position and orientation in the world) transformations.


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