Point Cloud Library (PCL) 1.14.0
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ransac.h
1/*
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37
38#pragma once
39
40#include <pcl/cuda/sample_consensus/sac.h>
41#include <pcl/cuda/sample_consensus/sac_model.h>
42
43namespace pcl
44{
45 namespace cuda
46 {
47 /** \brief @b RandomSampleConsensus represents an implementation of the
48 * RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Random
49 * Sample Consensus: A Paradigm for Model Fitting with Applications to Image
50 * Analysis and Automated Cartography", Martin A. Fischler and Robert C. Bolles,
51 * Comm. Of the ACM 24: 381–395, June 1981.
52 * \author Radu Bogdan Rusu
53 */
54 template <template <typename> class Storage>
55 class RandomSampleConsensus : public SampleConsensus<Storage>
56 {
58 using SampleConsensus<Storage>::threshold_;
59 using SampleConsensus<Storage>::iterations_;
60 using SampleConsensus<Storage>::sac_model_;
61 using SampleConsensus<Storage>::model_;
63 using SampleConsensus<Storage>::inliers_;
65 using SampleConsensus<Storage>::probability_;
66
67 using SampleConsensusModelPtr = typename SampleConsensusModel<Storage>::Ptr;
68 using Coefficients = typename SampleConsensusModel<Storage>::Coefficients;
69 using Indices = typename SampleConsensusModel<Storage>::Indices;
70 using Hypotheses = typename SampleConsensusModel<Storage>::Hypotheses;
71
72 public:
73 /** \brief RANSAC (RAndom SAmple Consensus) main constructor
74 * \param model a Sample Consensus model
75 */
76 RandomSampleConsensus (const SampleConsensusModelPtr &model) :
77 SampleConsensus<Storage> (model)
78 {
79 // Maximum number of trials before we give up.
80 max_iterations_ = 10000;
81 }
82
83 /** \brief RANSAC (RAndom SAmple Consensus) main constructor
84 * \param model a Sample Consensus model
85 * \param threshold distance to model threshold
86 */
87 RandomSampleConsensus (const SampleConsensusModelPtr &model, float threshold) :
88 SampleConsensus<Storage> (model, threshold)
89 {
90 // Maximum number of trials before we give up.
91 max_iterations_ = 10000;
92 }
93
94 /** \brief Compute the actual model and find the inliers
95 * \param debug_verbosity_level enable/disable on-screen debug
96 * information and set the verbosity level
97 */
98 bool
99 computeModel (int debug_verbosity_level = 0);
100 };
101 } // namespace
102} // namespace
RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm,...
Definition ransac.h:56
RandomSampleConsensus(const SampleConsensusModelPtr &model)
RANSAC (RAndom SAmple Consensus) main constructor.
Definition ransac.h:76
bool computeModel(int debug_verbosity_level=0)
Compute the actual model and find the inliers.
RandomSampleConsensus(const SampleConsensusModelPtr &model, float threshold)
RANSAC (RAndom SAmple Consensus) main constructor.
Definition ransac.h:87
IndicesPtr inliers_stencil_
Definition sac.h:180
Indices model_
The model found after the last computeModel () as point cloud indices.
Definition sac.h:176
float probability_
Desired probability of choosing at least one sample free from outliers.
Definition sac.h:186
float threshold_
Distance to model threshold.
Definition sac.h:192
int max_iterations_
Maximum number of iterations before giving up.
Definition sac.h:195
Coefficients model_coefficients_
The coefficients of our model computed directly from the model found.
Definition sac.h:183
IndicesPtr inliers_
The indices of the points that were chosen as inliers after the last call.
Definition sac.h:179
SampleConsensusModelPtr sac_model_
The underlying data model used (what is it that we attempt to search for).
Definition sac.h:173
int iterations_
Total number of internal loop iterations that we've done so far.
Definition sac.h:189
typename Storage< float4 >::type Hypotheses
Definition sac_model.h:105
typename Storage< float >::type Coefficients
Definition sac_model.h:101
typename Storage< int >::type Indices
Definition sac_model.h:97
shared_ptr< SampleConsensusModel > Ptr
Definition sac_model.h:94