%YAML:1.0

#--------------------------------------------------------------------------------------------
# Camera Parameters. Adjust them!
#--------------------------------------------------------------------------------------------
Camera.type: "PinHole"

# Camera calibration and distortion parameters (OpenCV) (equal for both cameras after stereo rectification)
Camera.fx: 1176.269294800212
Camera.fy: 1176.433529657170
Camera.cx: 604.755275885255
Camera.cy: 518.745152044285

Camera.k1: -0.050611950529281
Camera.k2: 0.097947651917225
Camera.p1: -0.000419283069591
Camera.p2: -0.000256740077382

Camera.width: 1224
Camera.height: 1024

# Camera frames per second 
Camera.fps: 10.0

# stereo baseline times fx (unit: m x pixel)
Camera.bf: 423.4569461280763

#--------------------------------------------------------------------------------------------
# IMU noise
#--------------------------------------------------------------------------------------------
IMU.NoiseGyro: 1.0216647894856925e-02
IMU.NoiseAcc: 1.1692699862662088e-02
IMU.GyroWalk: 8.4514305618965801e-05 
IMU.AccWalk: 2.0413058951725431e-04
IMU.Frequency: 100

# Transformation from left camera to imu
Tic: !!opencv-matrix
   rows: 4
   cols: 4
   dt: d
   data: [0.00464162, -0.00460674,  0.99997862,  0.12607916,
         -0.99998633,  0.00238464,  0.00465265,  0.15840427,
         -0.00240602, -0.99998655, -0.00459561,  0.03420431,
          0.0,         0.0,         0.0,         1.0]

#--------------------------------------------------------------------------------------------
# Stereo Rectification. Only if you need to pre-rectify the images.
#--------------------------------------------------------------------------------------------
LEFT.height: 1024
LEFT.width: 1224
LEFT.D: !!opencv-matrix
   rows: 1
   cols: 5
   dt: d
   data: [-0.050611950529281,0.097947651917225, -0.000419283069591, -0.000256740077382, 0.0]
LEFT.K: !!opencv-matrix
   rows: 3
   cols: 3
   dt: d
   data: [1176.269294800212,    0.0,            604.755275885255, 
             0.0,            1176.433529657170, 518.745152044285, 
             0.0,               0.0,              1.0]
LEFT.R:  !!opencv-matrix
   rows: 3
   cols: 3
   dt: d
   data: [1.0, 0.0, 0.0,
          0.0, 1.0, 0.0,
          0.0, 0.0, 1.0]
LEFT.Rf:  !!opencv-matrix
   rows: 3
   cols: 3
   dt: d
   data: [1.0, 0.0, 0.0, 
          0.0, 1.0, 0.0, 
          0.0, 0.0, 1.0]
LEFT.P:  !!opencv-matrix
   rows: 3
   cols: 4
   dt: d
   data: [1176.269294800212,    0.0,            604.755275885255, 0.0,  
             0.0,            1176.433529657170, 518.745152044285, 0.0,  
             0.0,               0.0,              1.0,            0.0]

RIGHT.height: 1024
RIGHT.width: 1224
RIGHT.D: !!opencv-matrix
   rows: 1
   cols: 5
   dt: d
   data: [-0.050529645625590,0.100118794704043, 0.000151706619184,  0.000159873014222, 0.0]
RIGHT.K: !!opencv-matrix
   rows: 3
   cols: 3
   dt: d
   data: [1175.693639535029,    0.0,            623.245979164071, 
             0.0,            1175.840447155871, 509.547575123268, 
             0.0,               0.0,              1.0]
RIGHT.R:  !!opencv-matrix
   rows: 3
   cols: 3
   dt: d
   data: [0.999989460071177,  -0.003980443093461,  -0.002288191280272,
          0.003974940022537,   0.999989208997031,  -0.002404525173381,
          0.002297737664012,   0.002395404406757,   0.999994491204504]
RIGHT.P:  !!opencv-matrix
   rows: 3
   cols: 4
   dt: d
   data: [1175.693639535029,    0.0,            623.245979164071, -361.0218672707261, 
             0.0,            1175.840447155871, 509.547575123268,   -1.0402438315106, 
             0.0,               0.0,              1.0,               4.6677007688895]

#--------------------------------------------------------------------------------------------
# Transformation from left camera to lidar
#--------------------------------------------------------------------------------------------
Tlc: !!opencv-matrix
   rows: 4
   cols: 4
   dt: d
   data: [0.024713433215212,  0.012207384934017, 0.999620040801399,  0.157411762651960,
         -0.999501495500661, -0.019349870412999, 0.024946803541596,  0.162961503982182,
          0.019647053485450, -0.999738246876688, 0.011723097767528, -0.169579219781922,
          0.0,                0.0,               0.0,                1.000000000000000]