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<li><a class="reference internal" href="#">Extracting indices from a PointCloud</a></li>
<li><a class="reference internal" href="#the-code">The code</a></li>
<li><a class="reference internal" href="#the-explanation">The explanation</a></li>
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<div class="section" id="extracting-indices-from-a-pointcloud">
<span id="extract-indices"></span><h1>Extracting indices from a PointCloud</h1>
<p>In this tutorial we will learn how to use an <span>ExtractIndices</span> filter to extract a subset of
points from a point cloud based on the indices output by a segmentation algorithm. In order to not complicate the
tutorial, the segmentation algorithm is not explained here. Please check
the <a class="reference internal" href="planar_segmentation.html#planar-segmentation"><span class="std std-ref">Plane model segmentation</span></a> tutorial for more information.</p>
<iframe title="Extracting indices from a PointCloud" width="480" height="390" src="https://www.youtube.com/embed/ZTK7NR1Xx4c?rel=0" frameborder="0" allowfullscreen></iframe></div>
<div class="section" id="the-code">
<h1>The code</h1>
<p>First, download the dataset <a class="reference external" href="https://raw.github.com/PointCloudLibrary/data/master/tutorials/table_scene_lms400.pcd">table_scene_lms400.pcd</a>
and save it somewhere to disk.</p>
<p>Then, create a file, let’s say, <code class="docutils literal notranslate"><span class="pre">extract_indices.cpp</span></code> in your favorite
editor, and place the following inside it:</p>
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85</pre></div></td><td class="code"><div class="highlight"><pre><span></span><span class="cp">#include</span> <span class="cpf">&lt;iostream&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/ModelCoefficients.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/io/pcd_io.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/point_types.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/sample_consensus/method_types.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/sample_consensus/model_types.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/segmentation/sac_segmentation.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/filters/voxel_grid.h&gt;</span><span class="cp"></span>
<span class="cp">#include</span> <span class="cpf">&lt;pcl/filters/extract_indices.h&gt;</span><span class="cp"></span>
<span class="kt">int</span>
<span class="nf">main</span> <span class="p">()</span>
<span class="p">{</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">PCLPointCloud2</span><span class="o">::</span><span class="n">Ptr</span> <span class="n">cloud_blob</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PCLPointCloud2</span><span class="p">),</span> <span class="n">cloud_filtered_blob</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PCLPointCloud2</span><span class="p">);</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">PointCloud</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;::</span><span class="n">Ptr</span> <span class="n">cloud_filtered</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PointCloud</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span><span class="p">),</span> <span class="n">cloud_p</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PointCloud</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span><span class="p">),</span> <span class="n">cloud_f</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PointCloud</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span><span class="p">);</span>
<span class="c1">// Fill in the cloud data</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">PCDReader</span> <span class="n">reader</span><span class="p">;</span>
<span class="n">reader</span><span class="p">.</span><span class="n">read</span> <span class="p">(</span><span class="s">&quot;table_scene_lms400.pcd&quot;</span><span class="p">,</span> <span class="o">*</span><span class="n">cloud_blob</span><span class="p">);</span>
<span class="n">std</span><span class="o">::</span><span class="n">cerr</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;PointCloud before filtering: &quot;</span> <span class="o">&lt;&lt;</span> <span class="n">cloud_blob</span><span class="o">-&gt;</span><span class="n">width</span> <span class="o">*</span> <span class="n">cloud_blob</span><span class="o">-&gt;</span><span class="n">height</span> <span class="o">&lt;&lt;</span> <span class="s">&quot; data points.&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
<span class="c1">// Create the filtering object: downsample the dataset using a leaf size of 1cm</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">VoxelGrid</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PCLPointCloud2</span><span class="o">&gt;</span> <span class="n">sor</span><span class="p">;</span>
<span class="n">sor</span><span class="p">.</span><span class="n">setInputCloud</span> <span class="p">(</span><span class="n">cloud_blob</span><span class="p">);</span>
<span class="n">sor</span><span class="p">.</span><span class="n">setLeafSize</span> <span class="p">(</span><span class="mf">0.01f</span><span class="p">,</span> <span class="mf">0.01f</span><span class="p">,</span> <span class="mf">0.01f</span><span class="p">);</span>
<span class="n">sor</span><span class="p">.</span><span class="n">filter</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_filtered_blob</span><span class="p">);</span>
<span class="c1">// Convert to the templated PointCloud</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">fromPCLPointCloud2</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_filtered_blob</span><span class="p">,</span> <span class="o">*</span><span class="n">cloud_filtered</span><span class="p">);</span>
<span class="n">std</span><span class="o">::</span><span class="n">cerr</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;PointCloud after filtering: &quot;</span> <span class="o">&lt;&lt;</span> <span class="n">cloud_filtered</span><span class="o">-&gt;</span><span class="n">width</span> <span class="o">*</span> <span class="n">cloud_filtered</span><span class="o">-&gt;</span><span class="n">height</span> <span class="o">&lt;&lt;</span> <span class="s">&quot; data points.&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
<span class="c1">// Write the downsampled version to disk</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">PCDWriter</span> <span class="n">writer</span><span class="p">;</span>
<span class="n">writer</span><span class="p">.</span><span class="n">write</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span> <span class="p">(</span><span class="s">&quot;table_scene_lms400_downsampled.pcd&quot;</span><span class="p">,</span> <span class="o">*</span><span class="n">cloud_filtered</span><span class="p">,</span> <span class="nb">false</span><span class="p">);</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">ModelCoefficients</span><span class="o">::</span><span class="n">Ptr</span> <span class="n">coefficients</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">ModelCoefficients</span> <span class="p">());</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">PointIndices</span><span class="o">::</span><span class="n">Ptr</span> <span class="n">inliers</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PointIndices</span> <span class="p">());</span>
<span class="c1">// Create the segmentation object</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">SACSegmentation</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span> <span class="n">seg</span><span class="p">;</span>
<span class="c1">// Optional</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setOptimizeCoefficients</span> <span class="p">(</span><span class="nb">true</span><span class="p">);</span>
<span class="c1">// Mandatory</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setModelType</span> <span class="p">(</span><span class="n">pcl</span><span class="o">::</span><span class="n">SACMODEL_PLANE</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setMethodType</span> <span class="p">(</span><span class="n">pcl</span><span class="o">::</span><span class="n">SAC_RANSAC</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setMaxIterations</span> <span class="p">(</span><span class="mi">1000</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setDistanceThreshold</span> <span class="p">(</span><span class="mf">0.01</span><span class="p">);</span>
<span class="c1">// Create the filtering object</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">ExtractIndices</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span> <span class="n">extract</span><span class="p">;</span>
<span class="kt">int</span> <span class="n">i</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">nr_points</span> <span class="o">=</span> <span class="p">(</span><span class="kt">int</span><span class="p">)</span> <span class="n">cloud_filtered</span><span class="o">-&gt;</span><span class="n">size</span> <span class="p">();</span>
<span class="c1">// While 30% of the original cloud is still there</span>
<span class="k">while</span> <span class="p">(</span><span class="n">cloud_filtered</span><span class="o">-&gt;</span><span class="n">size</span> <span class="p">()</span> <span class="o">&gt;</span> <span class="mf">0.3</span> <span class="o">*</span> <span class="n">nr_points</span><span class="p">)</span>
<span class="p">{</span>
<span class="c1">// Segment the largest planar component from the remaining cloud</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setInputCloud</span> <span class="p">(</span><span class="n">cloud_filtered</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">segment</span> <span class="p">(</span><span class="o">*</span><span class="n">inliers</span><span class="p">,</span> <span class="o">*</span><span class="n">coefficients</span><span class="p">);</span>
<span class="k">if</span> <span class="p">(</span><span class="n">inliers</span><span class="o">-&gt;</span><span class="n">indices</span><span class="p">.</span><span class="n">size</span> <span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">)</span>
<span class="p">{</span>
<span class="n">std</span><span class="o">::</span><span class="n">cerr</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;Could not estimate a planar model for the given dataset.&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
<span class="k">break</span><span class="p">;</span>
<span class="p">}</span>
<span class="c1">// Extract the inliers</span>
<span class="n">extract</span><span class="p">.</span><span class="n">setInputCloud</span> <span class="p">(</span><span class="n">cloud_filtered</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">setIndices</span> <span class="p">(</span><span class="n">inliers</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">setNegative</span> <span class="p">(</span><span class="nb">false</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">filter</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_p</span><span class="p">);</span>
<span class="n">std</span><span class="o">::</span><span class="n">cerr</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;PointCloud representing the planar component: &quot;</span> <span class="o">&lt;&lt;</span> <span class="n">cloud_p</span><span class="o">-&gt;</span><span class="n">width</span> <span class="o">*</span> <span class="n">cloud_p</span><span class="o">-&gt;</span><span class="n">height</span> <span class="o">&lt;&lt;</span> <span class="s">&quot; data points.&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
<span class="n">std</span><span class="o">::</span><span class="n">stringstream</span> <span class="n">ss</span><span class="p">;</span>
<span class="n">ss</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;table_scene_lms400_plane_&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">i</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;.pcd&quot;</span><span class="p">;</span>
<span class="n">writer</span><span class="p">.</span><span class="n">write</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span> <span class="p">(</span><span class="n">ss</span><span class="p">.</span><span class="n">str</span> <span class="p">(),</span> <span class="o">*</span><span class="n">cloud_p</span><span class="p">,</span> <span class="nb">false</span><span class="p">);</span>
<span class="c1">// Create the filtering object</span>
<span class="n">extract</span><span class="p">.</span><span class="n">setNegative</span> <span class="p">(</span><span class="nb">true</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">filter</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_f</span><span class="p">);</span>
<span class="n">cloud_filtered</span><span class="p">.</span><span class="n">swap</span> <span class="p">(</span><span class="n">cloud_f</span><span class="p">);</span>
<span class="n">i</span><span class="o">++</span><span class="p">;</span>
<span class="p">}</span>
<span class="k">return</span> <span class="p">(</span><span class="mi">0</span><span class="p">);</span>
<span class="p">}</span>
</pre></div>
</td></tr></table></div>
</div>
<div class="section" id="the-explanation">
<h1>The explanation</h1>
<p>Now, let’s break down the code piece by piece, skipping the obvious.</p>
<p>After the data has been loaded from the input .PCD file, we create a
<span>VoxelGrid</span> filter, to downsample the data. The rationale behind data
downsampling here is just to speed things up – less points means less time
needed to spend within the segmentation loop.</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></span> <span class="n">pcl</span><span class="o">::</span><span class="n">VoxelGrid</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PCLPointCloud2</span><span class="o">&gt;</span> <span class="n">sor</span><span class="p">;</span>
<span class="n">sor</span><span class="p">.</span><span class="n">setInputCloud</span> <span class="p">(</span><span class="n">cloud_blob</span><span class="p">);</span>
<span class="n">sor</span><span class="p">.</span><span class="n">setLeafSize</span> <span class="p">(</span><span class="mf">0.01f</span><span class="p">,</span> <span class="mf">0.01f</span><span class="p">,</span> <span class="mf">0.01f</span><span class="p">);</span>
<span class="n">sor</span><span class="p">.</span><span class="n">filter</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_filtered_blob</span><span class="p">);</span>
</pre></div>
</div>
<p>The next block of code deals with the parametric segmentation. To keep the
tutorial simple, its explanation will be skipped for now. Please see the
<strong>segmentation</strong> tutorials (in particular <a class="reference internal" href="planar_segmentation.html#planar-segmentation"><span class="std std-ref">Plane model segmentation</span></a>) for more
information.</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></span> <span class="n">pcl</span><span class="o">::</span><span class="n">ModelCoefficients</span><span class="o">::</span><span class="n">Ptr</span> <span class="n">coefficients</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">ModelCoefficients</span> <span class="p">());</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">PointIndices</span><span class="o">::</span><span class="n">Ptr</span> <span class="n">inliers</span> <span class="p">(</span><span class="k">new</span> <span class="n">pcl</span><span class="o">::</span><span class="n">PointIndices</span> <span class="p">());</span>
<span class="c1">// Create the segmentation object</span>
<span class="n">pcl</span><span class="o">::</span><span class="n">SACSegmentation</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span> <span class="n">seg</span><span class="p">;</span>
<span class="c1">// Optional</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setOptimizeCoefficients</span> <span class="p">(</span><span class="nb">true</span><span class="p">);</span>
<span class="c1">// Mandatory</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setModelType</span> <span class="p">(</span><span class="n">pcl</span><span class="o">::</span><span class="n">SACMODEL_PLANE</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setMethodType</span> <span class="p">(</span><span class="n">pcl</span><span class="o">::</span><span class="n">SAC_RANSAC</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setMaxIterations</span> <span class="p">(</span><span class="mi">1000</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">setDistanceThreshold</span> <span class="p">(</span><span class="mf">0.01</span><span class="p">);</span>
</pre></div>
</div>
<p>The line</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></span> <span class="n">pcl</span><span class="o">::</span><span class="n">ExtractIndices</span><span class="o">&lt;</span><span class="n">pcl</span><span class="o">::</span><span class="n">PointXYZ</span><span class="o">&gt;</span> <span class="n">extract</span><span class="p">;</span>
</pre></div>
</div>
<p>and</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></span> <span class="n">extract</span><span class="p">.</span><span class="n">setInputCloud</span> <span class="p">(</span><span class="n">cloud_filtered</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">setIndices</span> <span class="p">(</span><span class="n">inliers</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">setNegative</span> <span class="p">(</span><span class="nb">false</span><span class="p">);</span>
<span class="n">extract</span><span class="p">.</span><span class="n">filter</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_p</span><span class="p">);</span>
</pre></div>
</div>
<p>represent the actual indices <span>extraction filter</span>. To process multiple models, we
run the process in a loop, and after each model is extracted, we go back to
obtain the remaining points, and iterate. The <em>inliers</em> are obtained from the segmentation process, as follows:</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></span> <span class="n">seg</span><span class="p">.</span><span class="n">setInputCloud</span> <span class="p">(</span><span class="n">cloud_filtered</span><span class="p">);</span>
<span class="n">seg</span><span class="p">.</span><span class="n">segment</span> <span class="p">(</span><span class="o">*</span><span class="n">inliers</span><span class="p">,</span> <span class="o">*</span><span class="n">coefficients</span><span class="p">);</span>
</pre></div>
</div>
</div>
<div class="section" id="compiling-and-running-the-program">
<h1>Compiling and running the program</h1>
<p>Add the following lines to your CMakeLists.txt file:</p>
<div class="highlight-cmake notranslate"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12</pre></div></td><td class="code"><div class="highlight"><pre><span></span><span class="nb">cmake_minimum_required</span><span class="p">(</span><span class="s">VERSION</span> <span class="s">3.5</span> <span class="s">FATAL_ERROR</span><span class="p">)</span>
<span class="nb">project</span><span class="p">(</span><span class="s">extract_indices</span><span class="p">)</span>
<span class="nb">find_package</span><span class="p">(</span><span class="s">PCL</span> <span class="s">1.2</span> <span class="s">REQUIRED</span><span class="p">)</span>
<span class="nb">include_directories</span><span class="p">(</span><span class="o">${</span><span class="nv">PCL_INCLUDE_DIRS</span><span class="o">}</span><span class="p">)</span>
<span class="nb">link_directories</span><span class="p">(</span><span class="o">${</span><span class="nv">PCL_LIBRARY_DIRS</span><span class="o">}</span><span class="p">)</span>
<span class="nb">add_definitions</span><span class="p">(</span><span class="o">${</span><span class="nv">PCL_DEFINITIONS</span><span class="o">}</span><span class="p">)</span>
<span class="nb">add_executable</span> <span class="p">(</span><span class="s">extract_indices</span> <span class="s">extract_indices.cpp</span><span class="p">)</span>
<span class="nb">target_link_libraries</span> <span class="p">(</span><span class="s">extract_indices</span> <span class="o">${</span><span class="nv">PCL_LIBRARIES</span><span class="o">}</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>After you have made the executable, you can run it. Simply do:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ ./extract_indices
</pre></div>
</div>
<p>You will see something similar to:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">PointCloud</span> <span class="n">before</span> <span class="n">filtering</span><span class="p">:</span> <span class="mi">460400</span> <span class="n">data</span> <span class="n">points</span><span class="o">.</span>
<span class="n">PointCloud</span> <span class="n">after</span> <span class="n">filtering</span><span class="p">:</span> <span class="mi">41049</span> <span class="n">data</span> <span class="n">points</span><span class="o">.</span>
<span class="n">PointCloud</span> <span class="n">representing</span> <span class="n">the</span> <span class="n">planar</span> <span class="n">component</span><span class="p">:</span> <span class="mi">20164</span> <span class="n">data</span> <span class="n">points</span><span class="o">.</span>
<span class="n">PointCloud</span> <span class="n">representing</span> <span class="n">the</span> <span class="n">planar</span> <span class="n">component</span><span class="p">:</span> <span class="mi">12129</span> <span class="n">data</span> <span class="n">points</span><span class="o">.</span>
</pre></div>
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