This chapter gives an overview of the different 3D matching approaches available in HALCON.
As it is already contained in its name, the box finder can be used to
locate box-shaped objects in 3D data. Thereby, no model of the
object is needed as an input for the operator
, but only the dimensions of the boxes to be found.
As a result you can retrieve the pose of a gripping point, which can be
especially useful in the case of a bin picking application.
find_box_3d
( 1) | ( 2) |
The surface-based matching approach is suited to locate more complex objects
as well. The shape of these objects is passed to the operator
, or find_surface_model
respectively, in the form of a surface model. The poses
of the found object instances in the scene are then returned.
find_surface_model_image
Note that there are several different approaches when using surface-based
matching. For detailed explanations regarding when and how to use these
approaches, tips, tricks, and troubleshooting, have a look at the
technical note on Surface-Based Matching
.
( 1) | ( 2) | ( 3) |
In case an object can occur in the scene in different, deformed states
you can use a deformable surface model to locate the object in the
scene. If an instance of such an object is found by the operator
, the object model can be retrieved
featuring the respective deformation and pose.
find_deformable_surface_model
( 1) | ( 2) | ( 3) | ( 4) |
With shape-based matching, instances of a 3D CAD model are searched in 2D
images instead of 3D point clouds.
For this, the edges of the wanted object need to be clearly visible
in the image and the used camera needs to be calibrated beforehand.
As a result, the object pose is computed and returned by the operator
.
find_shape_model_3d
( 1) | ( 2) | ( 3) |
3D Gripping Point Detection is a deep-learning-based approach to detect gripping points on arbitrary objects in a 3D scene. For further information please see the chapter 3D Matching / 3D Gripping Point Detection.