NormalSpace.cpp
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3 /*
4 
5 Copyright (c) 2010--2018,
6 Fran├žois Pomerleau and Stephane Magnenat, ASL, ETHZ, Switzerland
7 You can contact the authors at <f dot pomerleau at gmail dot com> and
8 <stephane at magnenat dot net>
9 
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34 */
35 #include "NormalSpace.h"
36 
37 #include <algorithm>
38 #include <vector>
39 #include <unordered_map>
40 #include <random>
41 #include <ciso646>
42 #include <cmath>
43 #include <numeric>
44 
45 // NormalSpaceDataPointsFilter
46 template <typename T>
48  PointMatcher<T>::DataPointsFilter("NormalSpaceDataPointsFilter",
49  NormalSpaceDataPointsFilter::availableParameters(), params),
50  nbSample{Parametrizable::get<std::size_t>("nbSample")},
51  seed{Parametrizable::get<std::size_t>("seed")},
52  epsilon{Parametrizable::get<T>("epsilon")},
53  nbBucket{std::size_t(ceil(2.0 * M_PI / epsilon) * ceil(M_PI / epsilon))}
54 {
55 }
56 
57 template <typename T>
60 {
61  DataPoints output(input);
62  inPlaceFilter(output);
63  return output;
64 }
65 
66 //TODO: Add support for 2D by building histogram of polar coordinate with uniform sampling
67 
68 template <typename T>
70 {
71  //check dimension
72  const std::size_t featDim = cloud.features.rows();
73  if(featDim < 4) //3D case support only
74  {
75  std::cerr << "ERROR: NormalSpaceDataPointsFilter does not support 2D point cloud yet (does nothing)" << std::endl;
76  return;
77  }
78 
79  //Check number of points
80  const int nbPoints = cloud.getNbPoints();
81  if(nbSample >= std::size_t(nbPoints))
82  return;
83 
84  //Check if there is normals info
85  if (!cloud.descriptorExists("normals"))
86  throw InvalidField("OrientNormalsDataPointsFilter: Error, cannot find normals in descriptors.");
87 
88  const auto& normals = cloud.getDescriptorViewByName("normals");
89 
90  std::mt19937 gen(seed); //Standard mersenne_twister_engine seeded with seed
91 
92  //bucketed normal space
93  std::vector<std::vector<int> > idBuckets;
94  idBuckets.resize(nbBucket);
95 
96  std::vector<std::size_t> keepIndexes;
97  keepIndexes.reserve(nbSample);
98 
99  // Generate a random sequence of indices so that elements are placed in buckets in random order
100  std::vector<std::size_t> randIdcs(nbPoints);
101  std::iota(randIdcs.begin(), randIdcs.end(), 0);
102  std::shuffle(randIdcs.begin(), randIdcs.end(), gen);
103 
105  for (auto randIdx : randIdcs)
106  {
107  // Allow for slight approximiation errors
108  assert(normals.col(randIdx).head(3).norm() >= 1.0-0.00001);
109  assert(normals.col(randIdx).head(3).norm() <= 1.0+0.00001);
110  // Catch errors where theta will be NaN
111  assert((normals(2,randIdx) <= 1.0) && (normals(2,randIdx) >= -1.0));
112 
113  //Theta = polar angle in [0 ; pi]
114  const T theta = std::acos(normals(2, randIdx));
115  //Phi = azimuthal angle in [0 ; 2pi]
116  const T phi = std::fmod(std::atan2(normals(1, randIdx), normals(0, randIdx)) + 2. * M_PI, 2. * M_PI);
117 
118  // Catch normal space hashing errors
119  assert(bucketIdx(theta, phi) < nbBucket);
120  idBuckets[bucketIdx(theta, phi)].push_back(randIdx);
121  }
122 
123  // Remove empty buckets
124  idBuckets.erase(std::remove_if(idBuckets.begin(), idBuckets.end(),
125  [](const std::vector<int>& bucket) { return bucket.empty(); }),
126  idBuckets.end());
127 
129  for (std::size_t i=0; i<nbSample; i++)
130  {
131  // Get a random bucket
132  std::uniform_int_distribution<std::size_t> uniBucket(0,idBuckets.size()-1);
133  std::size_t curBucketIdx = uniBucket(gen);
134  std::vector<int>& curBucket = idBuckets[curBucketIdx];
135 
137  int idToKeep = curBucket[curBucket.size()-1];
138  curBucket.pop_back();
139  keepIndexes.push_back(static_cast<std::size_t>(idToKeep));
140 
141  // Remove the bucket if it is empty
142  if (curBucket.empty()) {
143  idBuckets.erase(idBuckets.begin()+curBucketIdx);
144  }
145  }
146 
147  //TODO: evaluate performances between this solution and sorting the indexes
148  // We build map of (old index to new index), in case we sample pts at the begining of the pointcloud
149  std::unordered_map<std::size_t, std::size_t> mapidx;
150  std::size_t idx = 0;
151 
153  for(std::size_t id : keepIndexes)
154  {
155  //retrieve index from lookup table if sampling in already switched element
156  if(id<idx)
157  id = mapidx[id];
158  //Switch columns id and idx
159  cloud.swapCols(idx, id);
160  //Maintain new index position
161  mapidx[idx] = id;
162  //Update index
163  ++idx;
164  }
165  cloud.conservativeResize(nbSample);
166 }
167 
168 template <typename T>
169 std::size_t NormalSpaceDataPointsFilter<T>::bucketIdx(T theta, T phi) const
170 {
171  //Theta = polar angle in [0 ; pi] and Phi = azimuthal angle in [0 ; 2pi]
172  assert( (theta >= 0.0) && (theta <= static_cast<T>(M_PI)) && "Theta not in [0, Pi]");
173  assert( (phi >= 0) && (phi <= 2*static_cast<T>(M_PI)) && "Phi not in [0, 2Pi]");
174 
175  // Wrap Theta at Pi
176  if (theta == static_cast<T>(M_PI)) { theta = 0.0; };
177  // Wrap Phi at 2Pi
178  if (phi == 2*static_cast<T>(M_PI)) { phi = 0.0; };
179  // block number block size element number
180  return static_cast<std::size_t>( floor(theta/epsilon) * ceil(2.0*M_PI/epsilon) + floor(phi/epsilon) );
181 }
182 
183 template struct NormalSpaceDataPointsFilter<float>;
NormalSpaceDataPointsFilter::bucketIdx
std::size_t bucketIdx(T theta, T phi) const
Definition: NormalSpace.cpp:169
PointMatcher::DataPoints::swapCols
void swapCols(Index iCol, Index jCol)
Swap column i and j in the point cloud, swap also features and descriptors if any....
Definition: pointmatcher/DataPoints.cpp:406
NormalSpaceDataPointsFilter::inPlaceFilter
virtual void inPlaceFilter(DataPoints &cloud)
Apply these filters to a point cloud without copying.
Definition: NormalSpace.cpp:69
build_map.T
T
Definition: build_map.py:34
PointMatcher::DataPoints::descriptorExists
bool descriptorExists(const std::string &name) const
Look if a descriptor with a given name exist.
Definition: pointmatcher/DataPoints.cpp:583
PointMatcher
Functions and classes that are dependant on scalar type are defined in this templatized class.
Definition: PointMatcher.h:130
PointMatcher::DataPoints
A point cloud.
Definition: PointMatcher.h:207
PointMatcher::DataPoints::InvalidField
An exception thrown when one tries to access features or descriptors unexisting or of wrong dimension...
Definition: PointMatcher.h:250
NormalSpaceDataPointsFilter::NormalSpaceDataPointsFilter
NormalSpaceDataPointsFilter(const Parameters &params=Parameters())
Definition: NormalSpace.cpp:47
align_sequence.params
params
Definition: align_sequence.py:13
PointMatcher::DataPointsFilter
A data filter takes a point cloud as input, transforms it, and produces another point cloud as output...
Definition: PointMatcher.h:440
PointMatcher::DataPoints::getNbPoints
unsigned getNbPoints() const
Return the number of points contained in the point cloud.
Definition: pointmatcher/DataPoints.cpp:158
PointMatcher::DataPoints::features
Matrix features
features of points in the cloud
Definition: PointMatcher.h:331
NormalSpace.h
PointMatcher::DataPoints::conservativeResize
void conservativeResize(Index pointCount)
Resize the cloud to pointCount points, conserving existing ones.
Definition: pointmatcher/DataPoints.cpp:328
NormalSpaceDataPointsFilter::Parameters
Parametrizable::Parameters Parameters
Definition: NormalSpace.h:49
PointMatcher::DataPoints::getDescriptorViewByName
ConstView getDescriptorViewByName(const std::string &name) const
Get a const view on a descriptor by name, throw an exception if it does not exist.
Definition: pointmatcher/DataPoints.cpp:555
NormalSpaceDataPointsFilter::filter
virtual DataPoints filter(const DataPoints &input)
Apply filters to input point cloud. This is the non-destructive version and returns a copy.
Definition: NormalSpace.cpp:59
NormalSpaceDataPointsFilter
Definition: NormalSpace.h:40


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autogenerated on Mon Jul 1 2024 02:22:43