How do you convert a spherical coordinate (θ, φ) into a position (x, y) on an equirectangular projection (also called \'geographic projection\')
If photos are taken from a fixed point, and the camera can only rotate its yaw and pitch around that point. Then we can consider a sphere of any radius (for the math, it is highly recommended to use a radius of 1). The photo will be a rectangular shape on this sphere (from perspective of the camera).
If you are looking at the horizon (equator), then vertical pixels account for latitude, and horizontal pixels account for longitude. For a simple panorama photo of the horizon there is not much of a problem:
Here we look at roughly the horizon of our world. That is, the camera has angle va = ~0. Then this is pretty straightforward, because if we know that the photo is 70 degrees wide and 40 degrees high, then we also know that the longitude range will be approximately 70 degrees and latitude range 40 degrees.
If we don't care about a slight distortion, then the formula to calculate the (longitude,latitude) from any pixel (x,y) from the photo would be easy:
photo_width_deg = 70
photo_height_deg = 30
photo_width_px = 1280
photo_height_px = 720
ha = 0
va = 0
longitude = photo_width_deg * (x - photo_width_px/2) / photo_width_px + ha
latitude = photo_height_deg * (y - photo_height_px/2) / photo_height_px + va
But this approximation does not work at all when we move the camera much more vertically:
So how do we transform a pixel from the picture at (x, y) to a (longitude, latitude) coordinate given a vertical/horizontal angle at which the photo was taken (va,ha)?
The important idea that solved the problem for me is this: you basically have two spheres:
You know the spherical coordinate of a point on the photo-sphere, and you want to know where this point is on the geo-sphere with the different camera-angle.
We have to realize that it is difficult to do any calculations between the two spheres using just spherical coordinates. The math for the cartesian coordinate system is much simpler. In the cartesian coordinate system we can easily rotate around any axis using rotation matrices that are multiplied with the coordinate vector [x,y,z] to get the rotated coordinate back.
Warning: Here it is very important to know that there are different conventions with regard to the meaning of x-axis, y-axis, and z-axis. It is uncertain which axis is the vertical one, and which one points where to. You just have to make a drawing for yourself and decide on this. If the result is wrong, it's probably because these are mixed up. The same goes for the theta and phi for spherical coordinates.
So the trick is to transform from photo-sphere to cartesian, then apply the rotations, and then go back to spherical coordinates:
[x,y,z] vectors).(ha,va).// Photo resolution
double img_w_px = 1280;
double img_h_px = 720;
// Camera field-of-view angles
double img_ha_deg = 70;
double img_va_deg = 40;
// Camera rotation angles
double hcam_deg = 230;
double vcam_deg = 60;
// Camera rotation angles in radians
double hcam_rad = hcam_deg/180.0*PI;
double vcam_rad = vcam_rad/180.0*PI;
// Rotation around y-axis for vertical rotation of camera
Matrix rot_y = {
cos(vcam_rad), 0, sin(vcam_rad),
0, 1, 0,
-sin(vcam_rad), 0, cos(vcam_rad)
};
// Rotation around z-axis for horizontal rotation of camera
Matrix rot_z = {
cos(hcam_rad), -sin(hcam_rad), 0,
sin(hcam_rad), cos(hcam_rad), 0,
0, 0, 1
};
Image img = load('something.png');
for(int i=0;i
Note, this is just some kind of pseudo-code. It is advised to use a matrix-library that handles your multiplications and rotations of matrices and vectors.