PointCloudDownsample Method |
Downsample the point cloud in-place
Namespace:
Zivid.NET
Assembly:
ZividCoreNET (in ZividCoreNET.dll) Version: 0.0.0.0
Syntax public PointCloud Downsample(
PointCloudDownsampling downsampling
)
Public Function Downsample (
downsampling As PointCloudDownsampling
) As PointCloud
public:
PointCloud^ Downsample(
PointCloudDownsampling downsampling
)
Parameters
- downsampling
- Type: Zivid.NETPointCloudDownsampling
This enum defines the size of the downsampled point cloud
Return Value
Type:
PointCloudRemarks
Downsampling is used to reduce the number of points in the point cloud. Downsampling is performed
by combining a 2x2, 3x3 or 4x4 region of pixels in the original point cloud to one pixel in the
new point cloud. A downsampling factor of 2x2 will reduce width and height each to half, and thus
the overall number of points to 1/4. 3x3 downsampling reduces width and height each to 1/3, and
the overall number of points to 1/9, and so on.
X, Y and Z coordinates are downsampled by computing the SNR^2 weighted average of each point in
the corresponding NxN region in the original point cloud, ignoring invalid (NaN) points. Color is
downsampled by computing the average value for each color channel in the NxN region. SNR value is
downsampled by computing the square root of the sum of SNR^2 of each valid (non-NaN) point in the
NxN region. If all points in the NxN region are invalid (NaN), the downsampled SNR is set to the
max SNR in the region.
Downsampling is performed on the compute device. The point cloud is modified in-place. Use
Downsampled(PointCloudDownsampling) if you want to downsample to a new PointCloud instance. Downsampling
can be repeated multiple times to further reduce the size of the point cloud, if desired.
Note that the width or height of the point cloud is not required to divide evenly by the
downsampling factor (2, 3 or 4). The new width and height equals the original width and height
divided by the downsampling factor, rounded down. In this case the remaining columns at the right
and/or rows at the bottom of the original point cloud are ignored.
See Also