[−][src]Function opencv::calib3d::reproject_image_to_3d

pub fn reproject_image_to_3d(
    disparity: &dyn ToInputArray, 
    _3d_image: &mut dyn ToOutputArray, 
    q: &dyn ToInputArray, 
    handle_missing_values: bool, 
    ddepth: i32
) -> Result<()>

Reprojects a disparity image to 3D space.

Parameters

  • disparity: Input single-channel 8-bit unsigned, 16-bit signed, 32-bit signed or 32-bit floating-point disparity image. The values of 8-bit / 16-bit signed formats are assumed to have no fractional bits. If the disparity is 16-bit signed format, as computed by @ref StereoBM or @ref StereoSGBM and maybe other algorithms, it should be divided by 16 (and scaled to float) before being used here.
  • _3dImage: Output 3-channel floating-point image of the same size as disparity. Each element of _3dImage(x,y) contains 3D coordinates of the point (x,y) computed from the disparity map. If one uses Q obtained by @ref stereoRectify, then the returned points are represented in the first camera's rectified coordinate system.
  • Q: inline formula perspective transformation matrix that can be obtained with @ref stereoRectify.
  • handleMissingValues: Indicates, whether the function should handle missing values (i.e. points where the disparity was not computed). If handleMissingValues=true, then pixels with the minimal disparity that corresponds to the outliers (see StereoMatcher::compute ) are transformed to 3D points with a very large Z value (currently set to 10000).
  • ddepth: The optional output array depth. If it is -1, the output image will have CV_32F depth. ddepth can also be set to CV_16S, CV_32S or CV_32F.

The function transforms a single-channel disparity map to a 3-channel image representing a 3D surface. That is, for each pixel (x,y) and the corresponding disparity d=disparity(x,y) , it computes:

block formula

See also

To reproject a sparse set of points {(x,y,d),...} to 3D space, use perspectiveTransform.

C++ default parameters

  • handle_missing_values: false
  • ddepth: -1