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Difference between revisions of "Imaging Information"
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Lots of information on calibrating the depth camera is available on the [http://www.ros.org/wiki/kinect_node ROS kinect_node page]. | Lots of information on calibrating the depth camera is available on the [http://www.ros.org/wiki/kinect_node ROS kinect_node page]. | ||
| − | From their data, a basic first order approximation for converting the raw 11-bit disparity value to a depth value in centimeters is: 100/(-0.00307 * rawDisparity + 3.33). This approximation is approximately 10 cm off at 4 m away, and less than 2 cm off within 2.5 m. A | + | From their data, a basic first order approximation for converting the raw 11-bit disparity value to a depth value in centimeters is: 100/(-0.00307 * rawDisparity + 3.33). This approximation is approximately 10 cm off at 4 m away, and less than 2 cm off within 2.5 m. |
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| + | A better approximation is given by Stéphane Magnenat in [https://groups.google.com/group/openkinect/browse_thread/thread/31351846fd33c78/e98a94ac605b9f21?lnk=gst&q=stephane&pli=1 this post]: distance = 0.1236 * tan(rawDisparity / 2842.5 + 1.1863) in meters. Adding a final offset term of -0.037 centers the original ROS data. The tan approximation has a sum squared difference of .33 cm while the 1/x approximation is about 1.7 cm. | ||
Once you have the distance using the measurement above A good approximation for converting (i, j, z) to (x,y,z) is: | Once you have the distance using the measurement above A good approximation for converting (i, j, z) to (x,y,z) is: | ||
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scaleFactor = .0021. | scaleFactor = .0021. | ||
These values were found by hand. | These values were found by hand. | ||
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== Color/Depth Mapping == | == Color/Depth Mapping == | ||
To enable accurate mapping between depth pixels ([http://en.wikipedia.org/wiki/Voxel voxels]) and color pixels and obtain colored point clouds, the intrinsics parameters of both depth and color cameras are required (focal distances, distortion coefficients and image center), but their relative position and orientation in the world coordinate frame also need to be estimated. A preliminary attempt to extract all these parameters in a semi-automatic way is described there [http://nicolas.burrus.name/index.php/Research/Kinect]. | To enable accurate mapping between depth pixels ([http://en.wikipedia.org/wiki/Voxel voxels]) and color pixels and obtain colored point clouds, the intrinsics parameters of both depth and color cameras are required (focal distances, distortion coefficients and image center), but their relative position and orientation in the world coordinate frame also need to be estimated. A preliminary attempt to extract all these parameters in a semi-automatic way is described there [http://nicolas.burrus.name/index.php/Research/Kinect]. | ||
Revision as of 20:36, 4 December 2010
RGB Camera
The RGB camera has a slightly larger angle of view than the Depth camera. For computer vision applications, tt can be calibrated using standard techniques, e.g from OpenCV.
Depth Camera
Lots of information on calibrating the depth camera is available on the ROS kinect_node page.
From their data, a basic first order approximation for converting the raw 11-bit disparity value to a depth value in centimeters is: 100/(-0.00307 * rawDisparity + 3.33). This approximation is approximately 10 cm off at 4 m away, and less than 2 cm off within 2.5 m.
A better approximation is given by Stéphane Magnenat in this post: distance = 0.1236 * tan(rawDisparity / 2842.5 + 1.1863) in meters. Adding a final offset term of -0.037 centers the original ROS data. The tan approximation has a sum squared difference of .33 cm while the 1/x approximation is about 1.7 cm.
Once you have the distance using the measurement above A good approximation for converting (i, j, z) to (x,y,z) is:
x = (i - w / 2) * (z + minDistance) * scaleFactor * (w/h) y = (j - h / 2) * (z + minDistance) * scaleFactor z = z Where minDistance = -10 scaleFactor = .0021. These values were found by hand.
Color/Depth Mapping
To enable accurate mapping between depth pixels (voxels) and color pixels and obtain colored point clouds, the intrinsics parameters of both depth and color cameras are required (focal distances, distortion coefficients and image center), but their relative position and orientation in the world coordinate frame also need to be estimated. A preliminary attempt to extract all these parameters in a semi-automatic way is described there [1].
