Point Cloud Library (PCL)  1.11.1-dev
occlusion_reasoning.hpp
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36 
37 #ifndef PCL_RECOGNITION_OCCLUSION_REASONING_HPP_
38 #define PCL_RECOGNITION_OCCLUSION_REASONING_HPP_
39 
40 #include <pcl/recognition/hv/occlusion_reasoning.h>
41 
42 #include <algorithm>
43 
44 ///////////////////////////////////////////////////////////////////////////////////////////
45 template<typename ModelT, typename SceneT>
47  f_ (f), cx_ (resx), cy_ (resy), depth_ (nullptr)
48 {
49 }
50 
51 ///////////////////////////////////////////////////////////////////////////////////////////
52 template<typename ModelT, typename SceneT>
54  f_ (), cx_ (), cy_ (), depth_ (nullptr)
55 {
56 }
57 
58 ///////////////////////////////////////////////////////////////////////////////////////////
59 template<typename ModelT, typename SceneT>
61 {
62  delete[] depth_;
63 }
64 
65 ///////////////////////////////////////////////////////////////////////////////////////////
66 template<typename ModelT, typename SceneT> void
68  typename pcl::PointCloud<ModelT>::Ptr & filtered, float thres)
69 {
70  pcl::Indices indices_to_keep;
71  filter(model, indices_to_keep, thres);
72  pcl::copyPointCloud (*model, indices_to_keep, *filtered);
73 }
74 
75 ///////////////////////////////////////////////////////////////////////////////////////////
76 template<typename ModelT, typename SceneT> void
78  pcl::Indices & indices_to_keep, float thres)
79 {
80 
81  float cx, cy;
82  cx = static_cast<float> (cx_) / 2.f - 0.5f;
83  cy = static_cast<float> (cy_) / 2.f - 0.5f;
84 
85  indices_to_keep.resize (model->size ());
86  int keep = 0;
87  for (std::size_t i = 0; i < model->size (); i++)
88  {
89  float x = (*model)[i].x;
90  float y = (*model)[i].y;
91  float z = (*model)[i].z;
92  int u = static_cast<int> (f_ * x / z + cx);
93  int v = static_cast<int> (f_ * y / z + cy);
94 
95  if (u >= cx_ || v >= cy_ || u < 0 || v < 0)
96  continue;
97 
98  //Check if point depth (distance to camera) is greater than the (u,v) meaning that the point is not visible
99  if ((z - thres) > depth_[u * cy_ + v] || !std::isfinite(depth_[u * cy_ + v]))
100  continue;
101 
102  indices_to_keep[keep] = static_cast<int> (i);
103  keep++;
104  }
105 
106  indices_to_keep.resize (keep);
107 }
108 
109 ///////////////////////////////////////////////////////////////////////////////////////////
110 template<typename ModelT, typename SceneT> void
112  bool smooth, int wsize)
113 {
114  float cx, cy;
115  cx = static_cast<float> (cx_) / 2.f - 0.5f;
116  cy = static_cast<float> (cy_) / 2.f - 0.5f;
117 
118  //compute the focal length
119  if (compute_focal)
120  {
121 
122  float max_u, max_v, min_u, min_v;
123  max_u = max_v = std::numeric_limits<float>::max () * -1;
124  min_u = min_v = std::numeric_limits<float>::max ();
125 
126  for (const auto& point: *scene)
127  {
128  float b_x = point.x / point.z;
129  if (b_x > max_u)
130  max_u = b_x;
131  if (b_x < min_u)
132  min_u = b_x;
133 
134  float b_y = point.y / point.z;
135  if (b_y > max_v)
136  max_v = b_y;
137  if (b_y < min_v)
138  min_v = b_y;
139  }
140 
141  float maxC = std::max (std::max (std::abs (max_u), std::abs (max_v)), std::max (std::abs (min_u), std::abs (min_v)));
142  f_ = (cx) / maxC;
143  }
144 
145  depth_ = new float[cx_ * cy_];
146  std::fill_n(depth_, cx * cy, std::numeric_limits<float>::quiet_NaN());
147 
148  for (const auto& point: *scene)
149  {
150  const float& x = point.x;
151  const float& y = point.y;
152  const float& z = point.z;
153  const int u = static_cast<int> (f_ * x / z + cx);
154  const int v = static_cast<int> (f_ * y / z + cy);
155 
156  if (u >= cx_ || v >= cy_ || u < 0 || v < 0)
157  continue;
158 
159  if ((z < depth_[u * cy_ + v]) || (!std::isfinite(depth_[u * cy_ + v])))
160  depth_[u * cx_ + v] = z;
161  }
162 
163  if (smooth)
164  {
165  //Dilate and smooth the depth map
166  int ws = wsize;
167  int ws2 = int (std::floor (static_cast<float> (ws) / 2.f));
168  float * depth_smooth = new float[cx_ * cy_];
169  for (int i = 0; i < (cx_ * cy_); i++)
170  depth_smooth[i] = std::numeric_limits<float>::quiet_NaN ();
171 
172  for (int u = ws2; u < (cx_ - ws2); u++)
173  {
174  for (int v = ws2; v < (cy_ - ws2); v++)
175  {
176  float min = std::numeric_limits<float>::max ();
177  for (int j = (u - ws2); j <= (u + ws2); j++)
178  {
179  for (int i = (v - ws2); i <= (v + ws2); i++)
180  {
181  if (std::isfinite(depth_[j * cx_ + i]) && (depth_[j * cx_ + i] < min))
182  {
183  min = depth_[j * cx_ + i];
184  }
185  }
186  }
187 
188  if (min < (std::numeric_limits<float>::max () - 0.1))
189  {
190  depth_smooth[u * cx_ + v] = min;
191  }
192  }
193  }
194 
195  memcpy (depth_, depth_smooth, sizeof(float) * cx_ * cy_);
196  delete[] depth_smooth;
197  }
198 }
199 
200 #endif // PCL_RECOGNITION_OCCLUSION_REASONING_HPP_
pcl::occlusion_reasoning::ZBuffering::~ZBuffering
~ZBuffering()
Definition: occlusion_reasoning.hpp:60
pcl::copyPointCloud
void copyPointCloud(const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out)
Copy all the fields from a given point cloud into a new point cloud.
Definition: io.hpp:144
pcl::occlusion_reasoning::ZBuffering::ZBuffering
ZBuffering()
Definition: occlusion_reasoning.hpp:53
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
pcl::PointCloud::size
std::size_t size() const
Definition: point_cloud.h:437
pcl::PointCloud::Ptr
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:407
pcl::occlusion_reasoning::ZBuffering::computeDepthMap
void computeDepthMap(typename pcl::PointCloud< SceneT >::ConstPtr &scene, bool compute_focal=false, bool smooth=false, int wsize=3)
Definition: occlusion_reasoning.hpp:111
pcl::PointCloud::ConstPtr
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:408
pcl::occlusion_reasoning::filter
pcl::PointCloud< ModelT >::Ptr filter(typename pcl::PointCloud< SceneT >::ConstPtr &organized_cloud, typename pcl::PointCloud< ModelT >::ConstPtr &to_be_filtered, float f, float threshold)
Definition: occlusion_reasoning.h:72
pcl::occlusion_reasoning::ZBuffering::filter
void filter(typename pcl::PointCloud< ModelT >::ConstPtr &model, typename pcl::PointCloud< ModelT >::Ptr &filtered, float thres=0.01)
Definition: occlusion_reasoning.hpp:67