| Operators |
create_surface_model — Create the data structure needed to perform surface-based matching.
create_surface_model( : : ObjectModel3D, RelSamplingDistance, GenParamName, GenParamValue : SurfaceModelID)
The operator create_surface_model creates a model for surface-based matching for the 3D object model ObjectModel3D. The 3D object model can, for example, have been read previously from a file by using read_object_model_3d, or been created by using xyz_to_object_model_3d. The created surface model is returned in SurfaceModelID.
Additional parameters of the surface model can be set with set_surface_model_param after the model was created.
The creation of the surface model requires that the 3D object model contains points and normals. The following combinations are possible:
points and point normals;
points and a triangular or polygon mesh, e.g., from a CAD file;
points and a 2D-Mapping, e.g., an XYZ image triple converted with xyz_to_object_model_3d.
Note that the direction and orientation (inward or outward) of the normals of the model are important for matching. Note also that for edge-supported surface-based matching, the model must contain a triangular or polygon mesh (see below).
The surface model is created by sampling the 3D object model with a certain distance. The sampling distance must be specified in the parameter RelSamplingDistance and is parametrized relative to the diameter of the axis-parallel bounding box of the 3D object model. For example, if RelSamplingDistance is set to 0.05 and the diameter of ObjectModel3D is '10 cm', the points sampled from the object's surface will be approximately '5 mm' apart. The sampled points are used for the approximate matching in the operator find_surface_model (see below). The sampled points can be obtained with the operator get_surface_model_param using the value 'sampled_model'. Note that outlier points in the object model should be avoided, as they would corrupt the diameter. Reducing RelSamplingDistance leads to more points, and in turn to a more stable but slower matching. Increasing RelSamplingDistance leads to less points, and in turn to a less stable but faster matching.
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The sampled points are used for finding the object model in a scene by using the operator find_surface_model. For this, all possible pairs of points from the point set are examined, and the distance and relative surface orientation of each pair is computed. Both values are discretized and stored for matching. The generic parameters 'feat_step_size_rel' and 'feat_angle_resolution' can be used to set the discretization of the distance and the orientation angles, respectively (see below).
The 3D object model is sampled a second time for the pose refinement. The second sampling is done with a smaller sampling distance, leading to more points. The generic parameter 'pose_ref_rel_sampling_distance' sets the sampling distance relative to the object's diameter. Decreasing the value results in a more accurate pose refinement but a larger model and a slower model generation and matching. Increasing the value leads to a less accurate pose refinement but a smaller model and faster model generation and matching (see below).
Surface-based matching can additionally use 3D edges to improve the alignment. This is particular helpful for objects that are planar or contain larger planar sides, such that they are found in incorrect rotations or in a background plane. In order to allow find_surface_model to also align edges, the surface model must be trained by setting the generic parameter 'train_3d_edges' to 'true'. In this case the model must contain a mesh, i.e. triangles or polygons. Also, the training for edge-supported surface-based matching requires OpenGL 2.1, GLSL 1.2, and the OpenGL extensions GL_EXT_framebuffer_object and GL_EXT_framebuffer_blit. It also can take significantly longer than training without edge-support.
The generic parameter pair GenParamName and GenParamValue are used to set additional parameters for the model generation. GenParamName contains the tuple of parameter names that shall be set and GenParamValue contains the corresponding values. The following values are possible for GenParamName:
Invert the orientation of the surface normals of the model. The normal orientation needs to be known for the model generation. If both the model and the scene are acquired with the same setup, the normals will already point in the same direction. If the model was loaded from a CAD file, the normals might point into the opposite direction. If you experience the effect that the model is found on the 'outside' of the scene surface and the model was created from a CAD file, try to set this parameter to 'true'. Also, make sure that the normals in the CAD file all point either outward or inward, i.e., are oriented consistently. The normal direction is irrelevant for the pose refinement of the surface model. Therefore, if the object model is only used with the operator refine_surface_model_pose, the value of 'model_invert_normals' has no effect on the result.
Possible values: 'false', 'true'
Default value: 'false'
Set the sampling distance for the pose refinement relative to the object's diameter. Decreasing this value leads to a more accurate pose refinement but a larger model and slower model generation and refinement. Increasing the value leads to a less accurate pose refinement but a smaller model and faster model generation and matching.
Suggested values: 0.05, 0.02, 0.01, 0.005
Default value: 0.01
Assertion: 0 < 'pose_ref_rel_sampling_distance' < 1
Set the discretization distance of the point pair distance relative to the object's diameter. This value defaults to the value of RelSamplingDistance. It is not recommended to change this value. For very noisy scenes, the value can be increased to improve the robustness of the matching against noisy points.
Suggested values: 0.1, 0.05, 0.03
Default value: Value of RelSamplingDistance
Assertion: 0 < 'feat_step_size_rel' < 1
Set the discretization of the point pair orientation as the number of subdivisions of the angle. It is recommended to not change this value. Increasing the value increases the precision of the matching but decreases the robustness against incorrect normal directions. Decreasing the value decreases the precision of the matching but increases the robustness against incorrect normal directions. For very noisy scenes where the normal directions can not be computed accurately, the value can be set to 25 or 20.
Suggested values: 20, 25, 30
Default value: 30
Assertion: 'feat_angle_resolution' > 1
Enable the training for edge-supported surface-based matching and refinement. In this case the model must contain a mesh, i.e. triangles or polygons. This parameter requires OpenGL.
Possible values: 'false', 'true'
Default value: 'false'
This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.
This operator supports cancelling timeouts.
Handle of the 3D object model.
Sampling distance relative to the object's diameter
Default value: 0.03
Suggested values: 0.1, 0.05, 0.03, 0.02, 0.01
Restriction: 0 < RelSamplingDistance < 1
Names of the generic parameters.
Default value: []
Suggested values: 'model_invert_normals', 'pose_ref_rel_sampling_distance', 'feat_step_size_rel', 'feat_angle_resolution', 'train_3d_edges'
Values of the generic parameters.
Default value: []
Suggested values: 0, 1, 'true', 'false', 0.005, 0.01, 0.02, 0.05, 0.1
Handle of the surface model.
create_surface_model returns 2 (H_MSG_TRUE) if all parameters are correct. If necessary, an exception is raised.
read_object_model_3d, xyz_to_object_model_3d, get_object_model_3d_params
find_surface_model, refine_surface_model_pose, get_surface_model_param, write_surface_model, clear_surface_model, set_surface_model_param
find_surface_model, refine_surface_model_pose, read_surface_model, write_surface_model, clear_surface_model, set_surface_model_param
Bertram Drost, Markus Ulrich, Nassir Navab, Slobodan Ilic: “Model Globally, Match Locally: Efficient and Robust 3D Object Recognition.” Computer Vision and Pattern Recognition, pp. 998-1005, 2010.
3D Metrology
| Operators |