Trait opencv::hub_prelude::PPF3DDetectorTrait

source · [−]
pub trait PPF3DDetectorTrait: PPF3DDetectorTraitConst {
    fn as_raw_mut_PPF3DDetector(&mut self) -> *mut c_void;

    fn set_search_params(
        &mut self, 
        position_threshold: f64, 
        rotation_threshold: f64, 
        use_weighted_clustering: bool
    ) -> Result<()> { ... }
    fn train_model(&mut self, model: &Mat) -> Result<()> { ... }
    fn match_(
        &mut self, 
        scene: &Mat, 
        results: &mut Vector<Pose3DPtr>, 
        relative_scene_sample_step: f64, 
        relative_scene_distance: f64
    ) -> Result<()> { ... }
}

Required Methods

Provided Methods

Set the parameters for the search

Parameters
  • positionThreshold: Position threshold controlling the similarity of translations. Depends on the units of calibration/model.
  • rotationThreshold: Position threshold controlling the similarity of rotations. This parameter can be perceived as a threshold over the difference of angles
  • useWeightedClustering: The algorithm by default clusters the poses without weighting. A non-zero value would indicate that the pose clustering should take into account the number of votes as the weights and perform a weighted averaging instead of a simple one.
C++ default parameters
  • position_threshold: -1
  • rotation_threshold: -1
  • use_weighted_clustering: false

\brief Trains a new model.

Parameters
  • Model: The input point cloud with normals (Nx6)

\details Uses the parameters set in the constructor to downsample and learn a new model. When the model is learnt, the instance gets ready for calling “match”.

source

fn match_(
    &mut self,
    scene: &Mat,
    results: &mut Vector<Pose3DPtr>,
    relative_scene_sample_step: f64,
    relative_scene_distance: f64
) -> Result<()>

\brief Matches a trained model across a provided scene.

Parameters
  • scene: Point cloud for the scene
  • results:[out] List of output poses
  • relativeSceneSampleStep: The ratio of scene points to be used for the matching after sampling with relativeSceneDistance. For example, if this value is set to 1.0/5.0, every 5th point from the scene is used for pose estimation. This parameter allows an easy trade-off between speed and accuracy of the matching. Increasing the value leads to less points being used and in turn to a faster but less accurate pose computation. Decreasing the value has the inverse effect.
  • relativeSceneDistance: Set the distance threshold relative to the diameter of the model. This parameter is equivalent to relativeSamplingStep in the training stage. This parameter acts like a prior sampling with the relativeSceneSampleStep parameter.
C++ default parameters
  • relative_scene_sample_step: 1.0/5.0
  • relative_scene_distance: 0.03

Implementors