Exporting estimated camera position and orientation

[yweidmann]

Dear list

Is there a way to access the estimated coordinates and orientations of each camera by scripting? Would like to write my own exporter to include some more information for each camera.

Looking forward to any hint,
Yvo

[Alexey Pasumansky]

Hello Yvo,

If you have georeferenced chunk, then the estimated camera position can be accessed using the following line:

Code: [Select]

chunk.crs.project(chunk.transform.matrix.mulp(camera.center))
Accessing the estimated orientation is a little but more complicated:

Code: [Select]

T = chunk.transform.matrix
m = chunk.crs.localframe(T.mulp(camera.center)) #transformation matrix to the LSE coordinates in the given point
R = m * T * camera.transform * PhotoScan.Matrix().Diag([1, -1, -1, 1])

row = list()
for j in range (0, 3): #creating normalized rotation matrix 3x3
    row.append(R.row(j))
    row[j].size = 3
    row[j].normalize()
R = PhotoScan.Matrix([row[0], row[1], row[2]])

yaw, pitch, roll = PhotoScan.utils.mat2ypr(R) #estimated orientation angles
print(yaw, pitch, roll)

[jiji]

Hello Alex,

I have the same question here and I understand gloabally the whole code that you gave.

But I don't really understand what the chunk.crs.localframe(gt) does exactlly ?
What does the result matrix mean ? and how we can get it from the geocentric point ?
could you give some details about the matrix calculation on this step ?


thx

[jiji]

Is the matrix return by crs.localframe(geocentricPoint) like below ? :

R = [ -sin L;               cos L;               0
         -sin N cos L;   -sin N sin L;   cos N
        -cos N cos L;  -cos N sin L;   -sinN
       ]


I found this matrix when my CRS is WGS 84. But there's some small difference when my CRS is some projection coordinates system.  where does these differences come from ?