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PointCloud.h
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26 
27 #pragma once
28 
29 #include <Eigen/Core>
30 #include <memory>
31 #include <tuple>
32 #include <vector>
33 
37 
38 namespace open3d {
39 
40 namespace camera {
41 class PinholeCameraIntrinsic;
42 }
43 
44 namespace geometry {
45 
46 class Image;
47 class RGBDImage;
48 class TriangleMesh;
49 class VoxelGrid;
50 
55 class PointCloud : public Geometry3D {
56 public:
62  PointCloud(const std::vector<Eigen::Vector3d> &points)
63  : Geometry3D(Geometry::GeometryType::PointCloud), points_(points) {}
64  ~PointCloud() override {}
65 
66 public:
67  PointCloud &Clear() override;
68  bool IsEmpty() const override;
69  Eigen::Vector3d GetMinBound() const override;
70  Eigen::Vector3d GetMaxBound() const override;
71  Eigen::Vector3d GetCenter() const override;
72  AxisAlignedBoundingBox GetAxisAlignedBoundingBox() const override;
73  OrientedBoundingBox GetOrientedBoundingBox(
74  bool robust = false) const override;
75  PointCloud &Transform(const Eigen::Matrix4d &transformation) override;
76  PointCloud &Translate(const Eigen::Vector3d &translation,
77  bool relative = true) override;
78  PointCloud &Scale(const double scale,
79  const Eigen::Vector3d &center) override;
80  PointCloud &Rotate(const Eigen::Matrix3d &R,
81  const Eigen::Vector3d &center) override;
82 
83  PointCloud &operator+=(const PointCloud &cloud);
84  PointCloud operator+(const PointCloud &cloud) const;
85 
87  bool HasPoints() const { return points_.size() > 0; }
88 
90  bool HasNormals() const {
91  return points_.size() > 0 && normals_.size() == points_.size();
92  }
93 
95  bool HasColors() const {
96  return points_.size() > 0 && colors_.size() == points_.size();
97  }
98 
100  bool HasCovariances() const {
101  return !points_.empty() && covariances_.size() == points_.size();
102  }
103 
106  for (size_t i = 0; i < normals_.size(); i++) {
107  normals_[i].normalize();
108  }
109  return *this;
110  }
111 
115  PointCloud &PaintUniformColor(const Eigen::Vector3d &color) {
116  ResizeAndPaintUniformColor(colors_, points_.size(), color);
117  return *this;
118  }
119 
128  PointCloud &RemoveNonFinitePoints(bool remove_nan = true,
129  bool remove_infinite = true);
130 
136  PointCloud &RemoveDuplicatedPoints();
137 
143  std::shared_ptr<PointCloud> SelectByIndex(
144  const std::vector<size_t> &indices, bool invert = false) const;
145 
151  std::shared_ptr<PointCloud> VoxelDownSample(double voxel_size) const;
152 
161  std::tuple<std::shared_ptr<PointCloud>,
162  Eigen::MatrixXi,
163  std::vector<std::vector<int>>>
164  VoxelDownSampleAndTrace(double voxel_size,
165  const Eigen::Vector3d &min_bound,
166  const Eigen::Vector3d &max_bound,
167  bool approximate_class = false) const;
168 
177  std::shared_ptr<PointCloud> UniformDownSample(size_t every_k_points) const;
178 
187  std::shared_ptr<PointCloud> RandomDownSample(double sampling_ratio) const;
188 
196  std::shared_ptr<PointCloud> FarthestPointDownSample(
197  size_t num_samples) const;
198 
205  std::shared_ptr<PointCloud> Crop(const AxisAlignedBoundingBox &bbox) const;
206 
213  std::shared_ptr<PointCloud> Crop(const OrientedBoundingBox &bbox) const;
214 
221  std::tuple<std::shared_ptr<PointCloud>, std::vector<size_t>>
222  RemoveRadiusOutliers(size_t nb_points,
223  double search_radius,
224  bool print_progress = false) const;
225 
231  std::tuple<std::shared_ptr<PointCloud>, std::vector<size_t>>
232  RemoveStatisticalOutliers(size_t nb_neighbors,
233  double std_ratio,
234  bool print_progress = false) const;
235 
246  void EstimateNormals(
247  const KDTreeSearchParam &search_param = KDTreeSearchParamKNN(),
248  bool fast_normal_computation = true);
249 
254  void OrientNormalsToAlignWithDirection(
255  const Eigen::Vector3d &orientation_reference =
256  Eigen::Vector3d(0.0, 0.0, 1.0));
257 
262  void OrientNormalsTowardsCameraLocation(
263  const Eigen::Vector3d &camera_location = Eigen::Vector3d::Zero());
264 
271  void OrientNormalsConsistentTangentPlane(size_t k);
272 
280  std::vector<double> ComputePointCloudDistance(const PointCloud &target);
281 
289  static std::vector<Eigen::Matrix3d> EstimatePerPointCovariances(
290  const PointCloud &input,
291  const KDTreeSearchParam &search_param = KDTreeSearchParamKNN());
292 
299  void EstimateCovariances(
300  const KDTreeSearchParam &search_param = KDTreeSearchParamKNN());
301 
304  std::tuple<Eigen::Vector3d, Eigen::Matrix3d> ComputeMeanAndCovariance()
305  const;
306 
311  std::vector<double> ComputeMahalanobisDistance() const;
312 
315  std::vector<double> ComputeNearestNeighborDistance() const;
316 
323  std::tuple<std::shared_ptr<TriangleMesh>, std::vector<size_t>>
324  ComputeConvexHull(bool joggle_inputs = false) const;
325 
335  std::tuple<std::shared_ptr<TriangleMesh>, std::vector<size_t>>
336  HiddenPointRemoval(const Eigen::Vector3d &camera_location,
337  const double radius) const;
338 
350  std::vector<int> ClusterDBSCAN(double eps,
351  size_t min_points,
352  bool print_progress = false) const;
353 
364  std::tuple<Eigen::Vector4d, std::vector<size_t>> SegmentPlane(
365  const double distance_threshold = 0.01,
366  const int ransac_n = 3,
367  const int num_iterations = 100,
368  const double probability = 0.99999999) const;
369 
389  static std::shared_ptr<PointCloud> CreateFromDepthImage(
390  const Image &depth,
391  const camera::PinholeCameraIntrinsic &intrinsic,
392  const Eigen::Matrix4d &extrinsic = Eigen::Matrix4d::Identity(),
393  double depth_scale = 1000.0,
394  double depth_trunc = 1000.0,
395  int stride = 1,
396  bool project_valid_depth_only = true);
397 
414  static std::shared_ptr<PointCloud> CreateFromRGBDImage(
415  const RGBDImage &image,
416  const camera::PinholeCameraIntrinsic &intrinsic,
417  const Eigen::Matrix4d &extrinsic = Eigen::Matrix4d::Identity(),
418  bool project_valid_depth_only = true);
419 
426  std::shared_ptr<PointCloud> CreateFromVoxelGrid(
427  const VoxelGrid &voxel_grid);
428 
429 public:
431  std::vector<Eigen::Vector3d> points_;
433  std::vector<Eigen::Vector3d> normals_;
435  std::vector<Eigen::Vector3d> colors_;
437  std::vector<Eigen::Matrix3d> covariances_;
438 };
439 
440 } // namespace geometry
441 } // namespace open3d
std::tuple< Eigen::Vector3d, Eigen::Matrix3d > ComputeMeanAndCovariance(const std::vector< Eigen::Vector3d > &points, const std::vector< IdxType > &indices)
Function to compute the mean and covariance matrix of a set of points.
Definition: Eigen.cpp:339
The base geometry class.
Definition: Geometry.h:37
bool HasCovariances() const
Returns &#39;true&#39; if the point cloud contains per-point covariance matrix.
Definition: PointCloud.h:100
A bounding box that is aligned along the coordinate axes.
Definition: BoundingVolume.h:155
Contains the pinhole camera intrinsic parameters.
Definition: PinholeCameraIntrinsic.h:51
A bounding box oriented along an arbitrary frame of reference.
Definition: BoundingVolume.h:44
A point cloud consists of point coordinates, and optionally point colors and point normals...
Definition: PointCloud.h:55
bool HasPoints() const
Returns &#39;true&#39; if the point cloud contains points.
Definition: PointCloud.h:87
int points
Definition: FilePCD.cpp:73
PointCloud & NormalizeNormals()
Normalize point normals to length 1.
Definition: PointCloud.h:105
std::vector< Eigen::Vector3d > points_
Points coordinates.
Definition: PointCloud.h:431
PointCloud()
Default Constructor.
Definition: PointCloud.h:58
math::float4 color
Definition: LineSetBuffers.cpp:64
PointCloud & PaintUniformColor(const Eigen::Vector3d &color)
Definition: PointCloud.h:115
std::vector< Eigen::Vector3d > colors_
RGB colors of points.
Definition: PointCloud.h:435
The base geometry class for 3D geometries.
Definition: Geometry3D.h:47
std::vector< Eigen::Matrix3d > covariances_
Covariance Matrix for each point.
Definition: PointCloud.h:437
Base class for KDTree search parameters.
Definition: KDTreeSearchParam.h:35
RGBDImage is for a pair of registered color and depth images,.
Definition: RGBDImage.h:46
size_t stride
Definition: TriangleMeshBuffers.cpp:184
std::vector< Eigen::Vector3d > normals_
Points normals.
Definition: PointCloud.h:433
bool HasNormals() const
Returns true if the point cloud contains point normals.
Definition: PointCloud.h:90
Definition: PinholeCameraIntrinsic.cpp:35
~PointCloud() override
Definition: PointCloud.h:64
VoxelGrid is a collection of voxels which are aligned in grid.
Definition: VoxelGrid.h:80
GeometryType
Specifies possible geometry types.
Definition: Geometry.h:42
Tensor operator+(T scalar_lhs, const Tensor &rhs)
Definition: Tensor.h:1415
bool HasColors() const
Returns true if the point cloud contains point colors.
Definition: PointCloud.h:95
KDTree search parameters for pure KNN search.
Definition: KDTreeSearchParam.h:63
PointCloud(const std::vector< Eigen::Vector3d > &points)
Parameterized Constructor.
Definition: PointCloud.h:62
The Image class stores image with customizable width, height, num of channels and bytes per channel...
Definition: Image.h:53
std::shared_ptr< core::Tensor > image
Definition: FilamentRenderer.cpp:202