Saliency.cpp
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1 // kate: replace-tabs off; indent-width 4; indent-mode normal
2 // vim: ts=4:sw=4:noexpandtab
3 /*
4 
5 Copyright (c) 2010--2018,
6 François 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 
10 All rights reserved.
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12 Redistribution and use in source and binary forms, with or without
13 modification, are permitted provided that the following conditions are met:
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22 
23 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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33 
34 */
35 #include "Saliency.h"
36 #include "utils/sparsetv.h"
37 
38 
39 // NormalSpaceDataPointsFilter
40 template <typename T>
42  PointMatcher<T>::DataPointsFilter("SaliencyDataPointsFilter",
43  SaliencyDataPointsFilter::availableParameters(), params),
44  k{Parametrizable::get<std::size_t>("k")},
45  sigma{Parametrizable::get<T>("sigma")},
46  keepNormals{Parametrizable::get<bool>("keepNormals")},
47  keepLabels{Parametrizable::get<bool>("keepLabels")},
48  keepTensors{Parametrizable::get<bool>("keepTensors")}
49 {
50 }
51 
52 template <typename T>
55 {
56  DataPoints output(input);
57  inPlaceFilter(output);
58  return output;
59 }
60 
61 template <typename T>
63 {
64  const std::size_t nbPts = cloud.getNbPoints();
65 
66  TensorVoting<T> tv{sigma, k};
67 
68  //Refinement step
69  tv.refine(cloud);
70 
71  //Compute real saliencies
72  tv.disableBallComponent();
73  tv.cfvote(cloud, false);
74  tv.decompose();
75  tv.toDescriptors();
76 
77  Matrix labels = Matrix::Zero(1, nbPts);
78  for(std::size_t i = 0; i < nbPts; ++i)
79  {
80  const T lambda1 = tv.surfaceness(i);
81  const T lambda2 = tv.curveness(i);
82  const T lambda3 = tv.pointness(i);
83 
84  int index;
85  Vector coeff = (Vector(3) << lambda3, (lambda2 - lambda3), (lambda1 - lambda2)).finished();
86  coeff.maxCoeff(&index);
87 
88  labels(i) = index + 1 ;
89  }
90 
91  try
92  {
93  cloud.addDescriptor("surfaceness", tv.surfaceness);
94  cloud.addDescriptor("curveness", tv.curveness);
95  cloud.addDescriptor("pointness", tv.pointness);
96 
97  if(keepNormals)
98  {
99  cloud.addDescriptor("normals", tv.normals);
100  cloud.addDescriptor("tangents", tv.tangents);
101  }
102  if(keepLabels)
103  {
104  cloud.addDescriptor("labels", labels);
105  }
106  if(keepTensors)
107  {
108  cloud.addDescriptor("sticks", tv.sticks);
109  cloud.addDescriptor("plates", tv.plates);
110  cloud.addDescriptor("balls", tv.balls);
111  }
112  }
113  catch (...) {
114  std::cerr << "SaliencyDataPointsFilter<T>::inPlaceFilter: Cannot add descriptors to pointcloud" << std::endl;
115  }
116 }
117 
118 template struct SaliencyDataPointsFilter<float>;
119 template struct SaliencyDataPointsFilter<double>;
SaliencyDataPointsFilter(const Parameters &params=Parameters())
Definition: Saliency.cpp:41
const std::size_t k
Definition: Saliency.h:78
unsigned getNbPoints() const
Return the number of points contained in the point cloud.
Parametrizable::Parameters Parameters
Definition: Saliency.h:49
const bool keepNormals
Definition: Saliency.h:80
Functions and classes that are dependant on scalar type are defined in this templatized class...
Definition: PointMatcher.h:130
const bool keepTensors
Definition: Saliency.h:82
A data filter takes a point cloud as input, transforms it, and produces another point cloud as output...
Definition: PointMatcher.h:440
const bool keepLabels
Definition: Saliency.h:81
virtual DataPoints filter(const DataPoints &input)
Apply filters to input point cloud. This is the non-destructive version and returns a copy...
Definition: Saliency.cpp:54
virtual void inPlaceFilter(DataPoints &cloud)
Apply these filters to a point cloud without copying.
Definition: Saliency.cpp:62
void addDescriptor(const std::string &name, const Matrix &newDescriptor)
Add a descriptor by name, remove first if already exists.


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autogenerated on Sat May 27 2023 02:38:03