ROS stereo_image_proc

이론 설명은 [요기]로

1. 설치

  • sudo apt-get install ros-indigo-stereo-image-proc
  • sudo apt-get install ros-melodic-stereo-image-proc

2. 실행

2.1 두개의 camera.launch 실행

cp camera.launch left_camera.launch
cp camera.launch right_camera.launch
vi left_camera.launch 
"""
   <!-- Determine this using rosrun pointgrey_camera_driver list_cameras.
       If not specified, defaults to first camera found. -->
  <arg name="camera_name" default="stereo/left" />  #stereo namespace필수 
  <arg name="camera_serial" default="18060129" />
  <arg name="calibrated" default="0" />
"""

  1. 각 launch 파일 실행

  2. image_rect_color를 활용 하므로

    • $ ~/.ros/camera_info/18060111.yaml & 18060129.yaml
    • $ ROS_NAMESPACE=stereo/left rosrun image_proc image_proc
    • $ ROS_NAMESPACE=stereo/right rosrun image_proc image_proc
    • rostopic echo /stereo/right/camera_info로 확인
  3. $ ROS_NAMESPACE=stereo rosrun stereo_image_proc stereo_image_proc _approximate_sync:=True

2.2 pointgrey 제공 stereo.launch 실행 (추천)

수정 항목

  • camera_name : camera -> stereo
  • frame_rate : 10 -> 1
  • camera_serial
<launch>
  <!-- Common parameters -->
  <arg name="camera_name" default="stereo" />
  <arg name="frame_rate" default="1" />

  <arg name="left_camera_serial" default="18060129" />
  <arg name="left_camera_calibrated" default="0" />

  <arg name="right_camera_serial" default="18060111" />
  <arg name="right_camera_calibrated" default="0" />
  1. roslaunch pointgrey_camera_driver stereo.launch
  2. <image_rect_color> 자동 생성
  3. <stereo_image_proc> 자동 실행 with _approximate_sync:=True

3. 시각화

출력

  • disparity images (stereo/disparity)
  • point clouds (stereo/points2).

3.1 Image

## rosrun image_view stereo_view stereo:=<stereo namespace> image:=<image topic identifier>
$ rosrun image_view stereo_view stereo:=/stereo image:=image_rect_color _queue_size:=20
# `rosnode info /stereo_view_{TAB}` 으로 확인

rivz이용 pintcloud2도 확인 가능

Choosing Good Stereo Parameters

Dynamic Reconfiture 활용 : rosrun rqt_reconfigure rqt_reconfigure

  • stereo_image_proc 선택

설정 값

Disparity pre-filtering

  • _prefilter_size (int, default: 9) : Normalization window size, pixels.
  • _prefilter_cap (int, default: 31) : Bound on normalized pixel values.

Disparity correlation

  • ~correlationwindow_size (int, default: 15) : Edge size (pixels) of the correlation window for matching. Values must be odd, in the range 5 to 255 (but with an extra performance hit for values larger than 21). Larger values have smoother disparity results, but smear out small features and depth discontinuities. ~min_disparity (int, default: 0) : Minimum disparity, or the offset to the disparity search window. By setting to a positive value, the cameras become more "cross-eyed" and will find objects closer to the cameras. If the cameras are "verged" (inclined toward each other), it may be appropriate to set min_disparity to a negative value. When min_disparity is greater than 0, objects at large distances will not be found.
  • ~disparity_range (int, default: 64) : The size of the disparity search window (pixels). Together with min_disparity, this defines the "horopter," the 3D volume that is visible to the stereo algorithm.

Disparity post-filtering

  • ~uniqueness_ratio (double, default: 15.0) : Filters disparity readings based on a comparison to the next-best correlation along the epipolar line. Matches where uniqueness_ratio > (best_match - next_match) / next_match are filtered out.
  • ~texture_threshold (int, default: 10) : Filters disparity readings based on the amount of texture in the correlation window.
  • ~speckle_size (int, default: 100) : Filters disparity regions that are less than this number of pixels. For example, a value of 100 means that all regions with fewer than 100 pixels will be rejected.
  • ~speckle_range (int, default: 4) : Groups disparity regions based on their connectedness. Disparities are grouped together in the same region if they are within this distance in pixels. ```

설정 예시

1. What's this junk on the tabletop?

문제 : 얼룩같은 잡음이 많음 해결 : speckle filter

  • speckle_size is the number of pixels below which a disparity blob is dismissed as "speckle."
  • speckle_range controls how close in value disparities must be to be considered part of the same blob.
  • eg. In this case the objects in the scene are relatively large, so we can crank speckle_size up to 1000 pixels

2. But where are the table and object?

문제 : 테이블과 대상 물건이 사라짐 원인 : the table is too close to the camera for the stereo block matcher to "see" it. 해결 : search range

  • disparity_range is how many pixels to slide the window over. The larger it is, the larger the range of visible depths, but more computation is required.
  • min_disparity controls the offset from the x-position of the left pixel at which to begin searching.

문제 : 병 왼쪽 뒤에 blank 생김 원인 : 오른쪽 카메라가 감지 못함 That area is visible to the left camera but occluded by the bottle in the right camera 해결 : disparity_range

  • min_disparity is normally set to zero, meaning the block matcher can "see" out to infinity.
    • If you have a pair of stereo cameras that are verged, or inclined towards each other, it's possible to have negative disparities and you might set min_disparity to a negative value.
    • If you want to detect objects very close to the camera (disparity > 128), you could set min_disparity to a positive value, shifting the horopter towards the camera and sacrificing far-field for near-field perception.

3. Other parameters

  • correlation_window_size controls the size of the sliding SAD (sum of absolute differences) window used to find matching points between the left and right images. Larger window sizes will smooth over small gaps in the disparity image but will also smear object boundaries. The default (15x15) is normally adequate; for comparison, this disparity image used correlation_window_size = 9 and has more gaps:

  • uniqueness_ratio controls another post-filtering step. If the best matching disparity is not sufficiently better than every other disparity in the search range, the pixel is filtered out. You can try tweaking this if texture_threshold and the speckle filtering are still letting through spurious matches.

  • prefilter_size and prefilter_cap control the pre-filtering phase, which normalizes image brightness and enhances texture in preparation for block matching. Normally you should not need to adjust these.

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