, including all inherited members.
| computeModelCoefficients(const std::vector< int > &samples, Eigen::VectorXf &model_coefficients) | pcl::SampleConsensusModelSphere< PointT > | [virtual] |
| computeVariance(const std::vector< double > &error_sqr_dists) | pcl::SampleConsensusModel< PointT > | [inline] |
| computeVariance() | pcl::SampleConsensusModel< PointT > | [inline] |
| pcl::ConstPtr typedef | pcl::SampleConsensusModel< PointT > | |
| pcl::SampleConsensusModelFromNormals::ConstPtr typedef | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | |
| countWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold) | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [virtual] |
| doSamplesVerifyModel(const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) | pcl::SampleConsensusModelSphere< PointT > | [virtual] |
| drawIndexSample(std::vector< int > &sample) | pcl::SampleConsensusModel< PointT > | [inline, protected] |
| drawIndexSampleRadius(std::vector< int > &sample) | pcl::SampleConsensusModel< PointT > | [inline, protected] |
| error_sqr_dists_ | pcl::SampleConsensusModel< PointT > | [protected] |
| getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [virtual] |
| getIndices() const | pcl::SampleConsensusModel< PointT > | [inline] |
| getInputCloud() const | pcl::SampleConsensusModel< PointT > | [inline] |
| getInputNormals() | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [inline] |
| getModelType() const | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [inline, virtual] |
| getNormalDistanceWeight() | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [inline] |
| getRadiusLimits(double &min_radius, double &max_radius) | pcl::SampleConsensusModel< PointT > | [inline] |
| getSamples(int &iterations, std::vector< int > &samples) | pcl::SampleConsensusModel< PointT > | [inline, virtual] |
| getSampleSize() const | pcl::SampleConsensusModel< PointT > | [inline] |
| getSamplesMaxDist(double &radius) | pcl::SampleConsensusModel< PointT > | [inline] |
| indices_ | pcl::SampleConsensusModel< PointT > | [protected] |
| input_ | pcl::SampleConsensusModel< PointT > | [protected] |
| isModelValid(const Eigen::VectorXf &model_coefficients) | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [protected, virtual] |
| isSampleGood(const std::vector< int > &samples) const | pcl::SampleConsensusModelSphere< PointT > | [protected, virtual] |
| max_sample_checks_ | pcl::SampleConsensusModel< PointT > | [protected, static] |
| normal_distance_weight_ | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [protected] |
| normals_ | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [protected] |
| operator=(const SampleConsensusModelSphere &source) | pcl::SampleConsensusModelSphere< PointT > | [inline] |
| optimizeModelCoefficients(const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) | pcl::SampleConsensusModelSphere< PointT > | [virtual] |
| PointCloud typedef | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | |
| PointCloudConstPtr typedef | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | |
| PointCloudNConstPtr typedef | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | |
| PointCloudNPtr typedef | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | |
| PointCloudPtr typedef | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | |
| ProgressiveSampleConsensus< PointT > class | pcl::SampleConsensusModel< PointT > | [friend] |
| projectPoints(const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) | pcl::SampleConsensusModelSphere< PointT > | [virtual] |
| Ptr typedef | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | |
| radius_max_ | pcl::SampleConsensusModel< PointT > | [protected] |
| radius_min_ | pcl::SampleConsensusModel< PointT > | [protected] |
| rnd() | pcl::SampleConsensusModel< PointT > | [inline, protected] |
| rng_alg_ | pcl::SampleConsensusModel< PointT > | [protected] |
| rng_dist_ | pcl::SampleConsensusModel< PointT > | [protected] |
| rng_gen_ | pcl::SampleConsensusModel< PointT > | [protected] |
| SampleConsensusModel(bool random=false) | pcl::SampleConsensusModel< PointT > | [inline, protected] |
| SampleConsensusModel(const PointCloudConstPtr &cloud, bool random=false) | pcl::SampleConsensusModel< PointT > | [inline] |
| SampleConsensusModel(const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false) | pcl::SampleConsensusModel< PointT > | [inline] |
| SampleConsensusModelFromNormals() | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [inline] |
| SampleConsensusModelNormalSphere(const PointCloudConstPtr &cloud, bool random=false) | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [inline] |
| SampleConsensusModelNormalSphere(const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false) | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [inline] |
| SampleConsensusModelSphere(const PointCloudConstPtr &cloud, bool random=false) | pcl::SampleConsensusModelSphere< PointT > | [inline] |
| SampleConsensusModelSphere(const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false) | pcl::SampleConsensusModelSphere< PointT > | [inline] |
| SampleConsensusModelSphere(const SampleConsensusModelSphere &source) | pcl::SampleConsensusModelSphere< PointT > | [inline] |
| samples_radius_ | pcl::SampleConsensusModel< PointT > | [protected] |
| samples_radius_search_ | pcl::SampleConsensusModel< PointT > | [protected] |
| SearchPtr typedef | pcl::SampleConsensusModel< PointT > | |
| selectWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers) | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [virtual] |
| setIndices(const boost::shared_ptr< std::vector< int > > &indices) | pcl::SampleConsensusModel< PointT > | [inline] |
| setIndices(const std::vector< int > &indices) | pcl::SampleConsensusModel< PointT > | [inline] |
| setInputCloud(const PointCloudConstPtr &cloud) | pcl::SampleConsensusModel< PointT > | [inline, virtual] |
| setInputNormals(const PointCloudNConstPtr &normals) | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [inline] |
| setNormalDistanceWeight(const double w) | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [inline] |
| setRadiusLimits(const double &min_radius, const double &max_radius) | pcl::SampleConsensusModel< PointT > | [inline] |
| setSamplesMaxDist(const double &radius, SearchPtr search) | pcl::SampleConsensusModel< PointT > | [inline] |
| shuffled_indices_ | pcl::SampleConsensusModel< PointT > | [protected] |
| ~SampleConsensusModel() | pcl::SampleConsensusModel< PointT > | [inline, virtual] |
| ~SampleConsensusModelFromNormals() | pcl::SampleConsensusModelFromNormals< PointT, PointNT > | [inline, virtual] |
| ~SampleConsensusModelNormalSphere() | pcl::SampleConsensusModelNormalSphere< PointT, PointNT > | [inline, virtual] |
| ~SampleConsensusModelSphere() | pcl::SampleConsensusModelSphere< PointT > | [inline, virtual] |