How to deal with outliers?

[ghost]

Hi Frank and others,

the "fastfusion" project is awesome! Thank you very much for sharing.
How do you deal with outliers, e.g. sparse point measurements away from an object? I am looking for a solution to be used with stereo cameras, which are not as precise as the pattern systems aka. Kinect.

Is there a process reducing the "occupancy probability" of a node (=Brick, or Voxel) if no measurements are put into it after some time?

Thanks again!

[sturmju]

Hi,

I think that there is already a simple outlier supression that ignores
voxels with very few observations. Frank is currently at ICRA but maybe he
can point you to the corresponding line in the source code..

Cheers
Jürgen

On Mon, Jun 2, 2014 at 8:45 PM, mojovski notifications@github.com wrote:

Hi Frank and others,

the "fastfusion" project is awesome! Thank you very much for sharing.
How do you deal with outliers, e.g. sparse point measurements away from an
object? I am looking for a solution to be used with stereo cameras, which
are not as precise as the pattern systems aka. Kinect.

Is there a process reducing the "occupancy probability" of a node (=Brick,
or Voxel) if no measurements are put into it after some time?

Thanks again!

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