jerryzeng/thirdParty
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
thirdParty/PCL 1.12.0/share/doc/pcl-1.12/tutorials/html/voxel_grid.html

344 lines
18 KiB
HTML
Raw Permalink Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

<!DOCTYPE html>
<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]-->
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Downsampling a PointCloud using a VoxelGrid filter &mdash; Point Cloud Library 1.12.0 documentation</title>
<script type="text/javascript" src="_static/js/modernizr.min.js"></script>
<script type="text/javascript" id="documentation_options" data-url_root="./" src="_static/documentation_options.js"></script>
<script type="text/javascript" src="_static/jquery.js"></script>
<script type="text/javascript" src="_static/underscore.js"></script>
<script type="text/javascript" src="_static/doctools.js"></script>
<script type="text/javascript" src="_static/language_data.js"></script>
<script type="text/javascript" src="_static/js/theme.js"></script>
<link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="_static/pygments.css" type="text/css" />
<link rel="index" title="Index" href="genindex.html" />
<link rel="search" title="Search" href="search.html" />
</head>
<body class="wy-body-for-nav">
<div class="wy-grid-for-nav">
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
<div class="wy-side-scroll">
<div class="wy-side-nav-search" >
<a href="index.html" class="icon icon-home"> Point Cloud Library
</a>
<div class="version">
1.12.0
</div>
<div role="search">
<form id="rtd-search-form" class="wy-form" action="search.html" method="get">
<input type="text" name="q" placeholder="Search docs" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
</div>
</div>
<div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="main navigation">
<!-- Local TOC -->
<div class="local-toc"><ul>
<li><a class="reference internal" href="#">Downsampling a PointCloud using a VoxelGrid filter</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>
<li><a class="reference internal" href="#compiling-and-running-the-program">Compiling and running the program</a></li>
</ul>
</div>
</div>
</div>
</nav>
<section data-toggle="wy-nav-shift" class="wy-nav-content-wrap">
<nav class="wy-nav-top" aria-label="top navigation">
<i data-toggle="wy-nav-top" class="fa fa-bars"></i>
<a href="index.html">Point Cloud Library</a>
</nav>
<div class="wy-nav-content">
<div class="rst-content">
<div role="navigation" aria-label="breadcrumbs navigation">
<ul class="wy-breadcrumbs">
<li><a href="index.html">Docs</a> &raquo;</li>
<li>Downsampling a PointCloud using a VoxelGrid filter</li>
<li class="wy-breadcrumbs-aside">
</li>
</ul>
<hr/>
</div>
<div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
<div itemprop="articleBody">
<div class="section" id="downsampling-a-pointcloud-using-a-voxelgrid-filter">
<span id="voxelgrid"></span><h1>Downsampling a PointCloud using a VoxelGrid filter</h1>
<p>In this tutorial we will learn how to downsample – that is, reduce the number
of points – a point cloud dataset, using a voxelized grid approach.</p>
<p>The <code class="docutils literal notranslate"><span class="pre">VoxelGrid</span></code> class that we’re about to present creates a <em>3D voxel grid</em>
(think about a voxel grid as a set of tiny 3D boxes in space) over the input
point cloud data. Then, in each <em>voxel</em> (i.e., 3D box), all the points present
will be approximated (i.e., <em>downsampled</em>) with their centroid. This approach
is a bit slower than approximating them with the center of the voxel, but it
represents the underlying surface more accurately.</p>
<iframe title="Downsampling a PointCloud using a VoxelGrid filter" width="480" height="390" src="https://www.youtube.com/embed/YHR6_OIxtFI?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">voxel_grid.cpp</span></code> in your favorite
editor, and place the following inside it:</p>
<div class="highlight-cpp notranslate"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34</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/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/filters/voxel_grid.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</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">PCLPointCloud2</span><span class="o">::</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">PCLPointCloud2</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="c1">// Replace the path below with the path where you saved your file</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</span><span class="p">);</span> <span class="c1">// Remember to download the file first!</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</span><span class="o">-&gt;</span><span class="n">width</span> <span class="o">*</span> <span class="n">cloud</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">pcl</span><span class="o">::</span><span class="n">getFieldsList</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud</span><span class="p">)</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;).&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</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</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</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">pcl</span><span class="o">::</span><span class="n">getFieldsList</span> <span class="p">(</span><span class="o">*</span><span class="n">cloud_filtered</span><span class="p">)</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;).&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">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="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="n">Eigen</span><span class="o">::</span><span class="n">Vector4f</span><span class="o">::</span><span class="n">Zero</span> <span class="p">(),</span> <span class="n">Eigen</span><span class="o">::</span><span class="n">Quaternionf</span><span class="o">::</span><span class="n">Identity</span> <span class="p">(),</span> <span class="nb">false</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.</p>
<p>The following lines of code will read the point cloud data from disk.</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></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="c1">// Replace the path below with the path where you saved your file</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</span><span class="p">);</span> <span class="c1">// Remember to download the file first!</span>
</pre></div>
</div>
<p>Then, a <em>pcl::VoxelGrid</em> filter is created with a leaf size of 1cm, the input
data is passed, and the output is computed and stored in <em>cloud_filtered</em>.</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</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</span><span class="p">);</span>
</pre></div>
</div>
<p>Finally, the data is written to disk for later inspection.</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></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="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="n">Eigen</span><span class="o">::</span><span class="n">Vector4f</span><span class="o">::</span><span class="n">Zero</span> <span class="p">(),</span> <span class="n">Eigen</span><span class="o">::</span><span class="n">Quaternionf</span><span class="o">::</span><span class="n">Identity</span> <span class="p">(),</span> <span class="nb">false</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">voxel_grid</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">${</span><span class="nv">PCL_DEFINITIONS</span><span class="o">}</span><span class="p">)</span>
<span class="nb">add_executable</span> <span class="p">(</span><span class="s">voxel_grid</span> <span class="s">voxel_grid.cpp</span><span class="p">)</span>
<span class="nb">target_link_libraries</span> <span class="p">(</span><span class="s">voxel_grid</span> <span class="o">${</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>$ ./voxel_grid
</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="p">(</span><span class="n">x</span> <span class="n">y</span> <span class="n">z</span> <span class="n">intensity</span> <span class="n">distance</span> <span class="n">sid</span><span class="p">)</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="p">(</span><span class="n">x</span> <span class="n">y</span> <span class="n">z</span> <span class="n">intensity</span> <span class="n">distance</span> <span class="n">sid</span><span class="p">)</span><span class="o">.</span>
</pre></div>
</div>
</div>
</div>
</div>
<footer>
<hr/>
<div role="contentinfo">
<p>
&copy; Copyright
</p>
</div>
Built with <a href="http://sphinx-doc.org/">Sphinx</a> using a <a href="https://github.com/rtfd/sphinx_rtd_theme">theme</a> provided by <a href="https://readthedocs.org">Read the Docs</a>.
</footer>
</div>
</div>
</section>
</div>
<script type="text/javascript">
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
</body>
</html>
Reference in New Issue View Git Blame Copy Permalink