ROS camera calibration sensor_ Msgs/camerainfo message data type and meaning

1. It's useful recently ros Camera calibration , I found a lot on the Internet and didn't find the calibration Output parameters Explanation , In the end Official website I saw it , Make a note , I hope you found that useful .

link ：sensor_msgs/CameraInfo Documentation (ros.org)

2. Relevant contents and explanations ：

#######################################################################
#                      Calibration Parameters                         #
#######################################################################
# These are fixed during camera calibration. Their values will be the #
# same in all messages until the camera is recalibrated. Note that    #
# self-calibrating systems may "recalibrate" frequently.              #
#                                                                     #
# The internal parameters can be used to warp a raw (distorted) image #
# to:                                                                 #
#   1. An undistorted image (requires D and K)                        #
#   2. A rectified image (requires D, K, R)                           #
# The projection matrix P projects 3D points into the rectified image.#
#######################################################################

# The image dimensions with which the camera was calibrated. Normally
# this will be the full camera resolution in pixels.

#  high  , Company ： Pixels 
uint32 height
#  wide  , Company ： Pixels 
uint32 width



# The distortion parameters, size depending on the distortion model.
# For "plumb_bob", the 5 parameters are: (k1, k2, t1, t2, k3).
#  Distortion parameters 
float64[] D

# Intrinsic camera matrix for the raw (distorted) images.
#  The internal parameters of the image without de distortion processing 
#     [fx  0 cx]
# K = [ 0 fy cy]
#     [ 0  0  1]
# Projects 3D points in the camera coordinate frame to 2D pixel
# coordinates using the focal lengths (fx, fy) and principal point
# (cx, cy).
float64[9]  K # 3x3 row-major matrix

# Rectification matrix (stereo cameras only)
#  For stereo cameras only , Usually a multi camera 
#  For polar alignment 
# A rotation matrix aligning the camera coordinate system to the ideal
# stereo image plane so that epipolar lines in both stereo images are
# parallel.
float64[9]  R # 3x3 row-major matrix

# Projection/camera matrix
#  Projection matrix ： To distort , After correction, the three-dimensional coordinate points in the world coordinate system are projected to the two-dimensional points in the pixel coordinate system 
#     [fx'  0  cx' Tx]
# P = [ 0  fy' cy' Ty]
#     [ 0   0   1   0]
# By convention, this matrix specifies the intrinsic (camera) matrix
#  of the processed (rectified) image. That is, the left 3x3 portion
#  is the normal camera intrinsic matrix for the rectified image.
# It projects 3D points in the camera coordinate frame to 2D pixel
#  coordinates using the focal lengths (fx', fy') and principal point
#  (cx', cy') - these may differ from the values in K.
#  Monocular camera ,tx=ty=0
# For monocular cameras, Tx = Ty = 0. Normally, monocular cameras will
#  also have R = the identity and P[1:3,1:3] = K.
#  Binocular camera 
# For a stereo pair, the fourth column [Tx Ty 0]' is related to the
#  position of the optical center of the second camera in the first
#  camera's frame. We assume Tz = 0 so both cameras are in the same
#  stereo image plane. The first camera always has Tx = Ty = 0. For
#  the right (second) camera of a horizontal stereo pair, Ty = 0 and
#  Tx = -fx' * B, where B is the baseline between the cameras.
# Given a 3D point [X Y Z]', the projection (x, y) of the point onto
#  the rectified image is given by:
#  [u v w]' = P * [X Y Z 1]'
#         x = u / w
#         y = v / w
#  This holds for both images of a stereo pair.
float64[12] P # 3x4 row-major matrix

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