Strange camera_info

[HowardWhile]

ISSUE TEMPLATE ver. 0.3.0

1. Which TurtleBot3 you have?

   • Waffle Pi

2. Which ROS is working with TurtleBot3?

   • ROS 1 Kinetic Kame

3. Which SBC(Single Board Computer) is working on TurtleBot3?

   • Raspberry Pi 3

4. Which OS you installed in SBC?

   • Raspbian

5. Which OS you installed in Remote PC?

   • Ubuntu 16.04 LTS (Xenial Xerus)

Hi ROBOTIS

When I try to initial raspberry pi camera by command.

roslaunch turtlebot3_bringup turtlebot3_rpicamera.launch

I found the camera parameter at "turtlebot3_bringup/camera_info/turtlebot3_rpicamera.yaml" is a little weird.

below is the parameters in the file.

image_width: 640
image_height: 480
camera_name: camera
camera_matrix:
  rows: 3
  cols: 3
  data: [322.0704122808738, 0, 199.2680620421962, 0, 320.8673986158544, 155.2533082600705, 0, 0, 1]
distortion_model: plumb_bob
distortion_coefficients:
  rows: 1
  cols: 5
  data: [0.1639958233797625, -0.271840030972792, 0.001055841660100477, -0.00166555973740089, 0]
rectification_matrix:
  rows: 3
  cols: 3
  data: [1, 0, 0, 0, 1, 0, 0, 0, 1]
projection_matrix:
  rows: 3
  cols: 4
  data: [329.2483825683594, 0, 198.4101510452074, 0, 0, 329.1044006347656, 155.5057121208347, 0, 0, 0, 1, 0]

the camera_matrix look like below

Refer to the description in opencv, is a principal point that is usually at the image center.

And Consider the image length and width is 640x480.

(199.26, 155.25) is a little far from the image center (320, 240).

So I tried to recalculate the camera parameters follow this tutorials. The new parameters as follows:

image_width: 640
image_height: 480
camera_name: camera
camera_matrix:
  rows: 3
  cols: 3
  data: [509.002395, 0.000000, 327.562293, 0.000000, 506.358721, 245.259233, 0.000000, 0.000000, 1.000000]
distortion_model: plumb_bob
distortion_coefficients:
  rows: 1
  cols: 5
  data: [0.183372, -0.312891, -0.001562, 0.005458, 0.000000]
rectification_matrix:
  rows: 3
  cols: 3
  data: [1.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 1.000000]
projection_matrix:
  rows: 3
  cols: 4
  data: [521.060059, 0.000000, 331.136252, 0.000000, 0.000000, 521.592163, 244.694909, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000]

Now I can calculate the correct tag posture through this camera_info.

The tag detection algorithm I use is this

Best Regards, and provide these messages for you.

[JaehyunShim]

@HowardWhile

Thank you very much. I tested as your advice and I've got a result similar to yours. We will discuss it in the team and update our package. Thank you so much for your contribution.

Regards,
Ryan