RemoveSensorBias.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 "RemoveSensorBias.h"
36 
37 #include "PointMatcherPrivate.h"
38 
39 #include <string>
40 #include <vector>
41 
42 #include <boost/format.hpp>
43 #include <ciso646>
44 #include <cmath>
45 
46 
47 template<typename T>
49  PointMatcher<T>::DataPointsFilter("RemoveSensorBiasDataPointsFilter",
50  RemoveSensorBiasDataPointsFilter::availableParameters(), params),
51  sensorType(SensorType(Parametrizable::get<int>("sensorType"))),
52  angleThreshold(Parametrizable::get<T>("angleThreshold")/180.*M_PI)
53 {
54 }
55 
56 template<typename T>
59 {
60  DataPoints output(input);
61  inPlaceFilter(output);
62  return output;
63 }
64 
65 template<typename T>
67 {
68  //Check if there is normals info
69  if (!cloud.descriptorExists("incidenceAngles"))
70  throw InvalidField("RemoveSensorBiasDataPointsFilter: Error, cannot find incidence angles in descriptors.");
71  //Check if there is normals info
72  if (!cloud.descriptorExists("observationDirections"))
73  throw InvalidField("RemoveSensorBiasDataPointsFilter: Error, cannot find observationDirections in descriptors.");
74 
75  const auto& incidenceAngles = cloud.getDescriptorViewByName("incidenceAngles");
76  const auto& observationDirections = cloud.getDescriptorViewByName("observationDirections");
77 
78  double aperture, k1, k2;
79 
80  switch(sensorType)
81  {
82  case LMS_1XX:
83  {
84  aperture = SensorParameters::LMS_1XX.aperture;
85  k1 = SensorParameters::LMS_1XX.k1;
86  k2 = SensorParameters::LMS_1XX.k2;
87  break;
88  }
89  case HDL_32E:
90  {
91  aperture = SensorParameters::HDL_32E.aperture;
92  k1 = SensorParameters::HDL_32E.k1;
93  k2 = SensorParameters::HDL_32E.k2;
94  break;
95  }
96  default:
97  throw InvalidParameter(
98  (boost::format("RemoveSensorBiasDataPointsFilter: Error, cannot remove bias for sensorType id %1% .") % sensorType).str());
99  }
100 
101  const std::size_t nbPts = cloud.getNbPoints();
102  const std::size_t dim = cloud.features.rows();
103 
104 
105  assert(dim == 3 or dim == 4); //check 2D or 3D
106 
107  std::size_t j = 0;
108  for(std::size_t i = 0; i < nbPts; ++i)
109  {
110  const Vector vObs = observationDirections.col(i);
111 
112  const double depth = vObs.norm();
113  const T incidence = incidenceAngles(0, i);
114 
115  //check if the incidence angle could be estimated.
116  //For angles very close to 90 degrees, a small error of estimation could change drastically the correction, so we skip those points.
117  if(not std::isnan(incidence) and incidence >= 0. and incidence < angleThreshold)
118  {
119  const double correction = k1 * diffDist(depth, incidence, aperture) + k2 * ratioCurvature(depth, incidence, aperture);
120 
121  Vector p = cloud.features.col(i);
122  p.head(dim-1) += correction * vObs.normalized();
123  cloud.features.col(i) = p;
124  cloud.setColFrom(j, cloud, i);
125  ++j;
126  }
127  }
128  cloud.conservativeResize(j);
129 }
130 
131 template<typename T>
132 std::array<double, 4> RemoveSensorBiasDataPointsFilter<T>::getCoefficients(const double depth, const T theta, const double aperture) const
133 {
134  const double sigma = tau / std::sqrt(2. * M_PI);
135  const double w0 = lambda_light / (M_PI * aperture);
136 
137  const double A = 2. * std::pow(depth * std::tan(theta), 2) / std::pow(sigma * c, 2) + 2. / std::pow(aperture, 2);
138  const double K1 = std::pow(std::cos(theta), 3);
139  const double K2 = 3. * std::pow(std::cos(theta), 2) * std::sin(theta);
140  const double L1 = pulse_intensity * std::pow(w0 / (aperture * depth * std::cos(theta)), 2) *
141  std::sqrt(M_PI) * std::erf(aperture * std::sqrt(A)) / (2. * std::pow(A, 3. / 2.));
142  const double L2 = pulse_intensity * std::pow(w0 / (aperture * depth * std::cos(theta)), 2) * K2 / (2. * A);
143 
144  const double a0 = 2. * A * K1 * L1;
145  const double a1 = -(2. * std::tan(theta) * depth *
146  (L1 * K2 - 2. * L2 * aperture * std::exp(-A * std::pow(aperture, 2)))) / (std::pow(sigma, 2) * c);
147  const double a2 = -L1 * 2. * A * K1 * (std::pow(sigma * c * std::cos(theta), 2) * A + 2. * std::pow(std::cos(theta) * depth, 2) - 2. * std::pow(depth, 2)) /
148  (2 * std::pow(c * std::cos(theta), 2) * std::pow(sigma, 4) * A);
149  const double a3 = L1 * K2 * depth * std::tan(theta) * (std::pow(sigma * c, 2) * A - 2. * std::pow(depth * std::tan(theta), 2)) /
150  (std::pow(sigma, 6) * std::pow(c, 3) * A);
151 
152  return {a0, a1, a2, a3};
153 }
154 
155 template<typename T>
156 double RemoveSensorBiasDataPointsFilter<T>::diffDist(const double depth, const T theta, const double aperture) const
157 {
158  static constexpr double epsilon = 1e-5;
159 
160  const std::array<double, 4> a = getCoefficients(depth, theta, aperture);
161 
162  double Tmax;
163 
164  if(theta < epsilon) // approx. 0
165  Tmax = 0.;
166  else // theta >0
167  Tmax = (-2 * a[2] - std::sqrt(4 * pow(a[2], 2) - 12 * a[1] * a[3])) / (6 * a[3]);
168 
169  return Tmax * c / 2.;
170 }
171 
172 template<typename T>
173 double RemoveSensorBiasDataPointsFilter<T>::ratioCurvature(const double depth, const T theta, const double aperture) const
174 {
175  static constexpr double epsilon = 1e-5;
176  const std::array<double,4> a = getCoefficients(depth, theta, aperture);
177  const std::array<double,4> b = getCoefficients(depth, 0., aperture);
178 
179  double Tmax;
180 
181  if(theta < epsilon) // approx. 0
182  Tmax = 0.;
183  else // theta >0
184  Tmax = ( -2 * a[2] - std::sqrt(4 * std::pow(a[2], 2) - 12 * a[1] * a[3])) / (6 * a[3]);
185 
186  return 1. - 2 * b[2] / (2 * a[2] + 6 * Tmax * a[3]);
187 }
188 
RemoveSensorBiasDataPointsFilter::inPlaceFilter
virtual void inPlaceFilter(DataPoints &cloud)
Apply these filters to a point cloud without copying.
Definition: RemoveSensorBias.cpp:66
build_map.T
T
Definition: build_map.py:34
RemoveSensorBiasDataPointsFilter::Parameters
Parametrizable::Parameters Parameters
Definition: RemoveSensorBias.h:45
PointMatcher::DataPoints::descriptorExists
bool descriptorExists(const std::string &name) const
Look if a descriptor with a given name exist.
Definition: pointmatcher/DataPoints.cpp:583
RemoveSensorBiasDataPointsFilter
Definition: RemoveSensorBias.h:41
PointMatcher
Functions and classes that are dependant on scalar type are defined in this templatized class.
Definition: PointMatcher.h:130
PointMatcherPrivate.h
PointMatcher::DataPoints
A point cloud.
Definition: PointMatcher.h:207
RemoveSensorBiasDataPointsFilter::Vector
PM::Vector Vector
Definition: RemoveSensorBias.h:54
RemoveSensorBiasDataPointsFilter::filter
virtual DataPoints filter(const DataPoints &input)
Apply filters to input point cloud. This is the non-destructive version and returns a copy.
Definition: RemoveSensorBias.cpp:58
RemoveSensorBias.h
PointMatcher::DataPoints::InvalidField
An exception thrown when one tries to access features or descriptors unexisting or of wrong dimension...
Definition: PointMatcher.h:250
RemoveSensorBiasDataPointsFilter::RemoveSensorBiasDataPointsFilter
RemoveSensorBiasDataPointsFilter(const Parameters &params=Parameters())
Definition: RemoveSensorBias.cpp:48
align_sequence.params
params
Definition: align_sequence.py:13
RemoveSensorBiasDataPointsFilter::getCoefficients
std::array< double, 4 > getCoefficients(const double depth, const T theta, const double aperture) const
Definition: RemoveSensorBias.cpp:132
PointMatcher::DataPoints::setColFrom
void setColFrom(Index thisCol, const DataPoints &that, Index thatCol)
Set column thisCol equal to column thatCol of that, copy features and descriptors if any....
Definition: pointmatcher/DataPoints.cpp:393
PointMatcher::DataPointsFilter
A data filter takes a point cloud as input, transforms it, and produces another point cloud as output...
Definition: PointMatcher.h:440
InvalidParameter
Parametrizable::InvalidParameter InvalidParameter
Definition: pypoint_matcher_helper.h:42
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
PointMatcherSupport::Parametrizable
The superclass of classes that are constructed using generic parameters. This class provides the para...
Definition: Parametrizable.h:141
PointMatcherSupport::get
const M::mapped_type & get(const M &m, const typename M::key_type &k)
Definition: Bibliography.cpp:57
icp_advance_api.dim
dim
Definition: icp_advance_api.py:152
RemoveSensorBiasDataPointsFilter::ratioCurvature
double ratioCurvature(const double depth, const T theta, const double aperture) const
Definition: RemoveSensorBias.cpp:173
PointMatcher::DataPoints::conservativeResize
void conservativeResize(Index pointCount)
Resize the cloud to pointCount points, conserving existing ones.
Definition: pointmatcher/DataPoints.cpp:328
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
PointMatcherSupport::pow
constexpr T pow(const T base, const std::size_t exponent)
Definition: utils.h:47
RemoveSensorBiasDataPointsFilter::diffDist
double diffDist(const double depth, const T theta, const double aperture) const
Definition: RemoveSensorBias.cpp:156
RemoveSensorBiasDataPointsFilter::SensorType
SensorType
Definition: RemoveSensorBias.h:80


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