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<div id="projectname">RTAB-Map<span id="projectnumber">&#160;0.23.12</span>
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<div id="projectbrief">Real-Time Appearance-Based Mapping</div>
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<div class="textblock">Here is a list of all topics with brief descriptions:</div><div class="directory">
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<tr id="row_0_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__RoiComputation.html" target="_self">Region of Interest (ROI) Computation</a></td><td class="desc"></td></tr>
<tr id="row_1_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__LaserScanFromPointCloud.html" target="_self">PCL to 3D LaserScan</a></td><td class="desc">Converts various PCL point cloud types into a unified <a class="el" href="classrtabmap_1_1LaserScan.html" title="Represents 2D or 3D laser scan data with support for multiple point data formats.">LaserScan</a> format </td></tr>
<tr id="row_2_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__LaserScan2dFromPointCloud.html" target="_self">PCL to 2D LaserScan</a></td><td class="desc">Converts various PCL point cloud types into a unified 2D <a class="el" href="classrtabmap_1_1LaserScan.html" title="Represents 2D or 3D laser scan data with support for multiple point data formats.">LaserScan</a> format </td></tr>
<tr id="row_3_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__LaserScanToPointCloud.html" target="_self">LaserScan to PCL</a></td><td class="desc">Functions to convert <a class="el" href="classrtabmap_1_1LaserScan.html" title="Represents 2D or 3D laser scan data with support for multiple point data formats.">LaserScan</a> data to various PCL point cloud formats </td></tr>
<tr id="row_4_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__PointCloudRangeFiltering.html" target="_self">Range Filtering of PCL Point Clouds</a></td><td class="desc">Filters a point cloud based on a minimum and maximum Euclidean range </td></tr>
<tr id="row_5_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__PointCloudSplitRangeFiltering.html" target="_self">Split Range Filtering of PCL Point Clouds</a></td><td class="desc">Splits a point cloud into two groups based on a distance threshold </td></tr>
<tr id="row_6_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__PointCloudDownSampling.html" target="_self">Point Cloud Downsampling</a></td><td class="desc">Downsamples a point cloud or <a class="el" href="classrtabmap_1_1LaserScan.html" title="Represents 2D or 3D laser scan data with support for multiple point data formats.">LaserScan</a> by keeping only every N-th point </td></tr>
<tr id="row_7_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__VoxelFiltering.html" target="_self">Voxel Filtering</a></td><td class="desc">Performs voxel grid downsampling on a point cloud with optional index filtering </td></tr>
<tr id="row_8_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__RandomSampling.html" target="_self">Random Sampling</a></td><td class="desc">Randomly samples a subset of points from the input point cloud </td></tr>
<tr id="row_9_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__PassThrough.html" target="_self">Pass-through Filtering</a></td><td class="desc">Filters points from the input point cloud using a pass-through filter along a specified axis </td></tr>
<tr id="row_10_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__CropBox.html" target="_self">Crop Box Filtering</a></td><td class="desc">Filters points from a point cloud using a 3D crop box </td></tr>
<tr id="row_11_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__FrustumFiltering.html" target="_self">Frustum Filtering</a></td><td class="desc">Filters points from a point cloud based on a camera frustum </td></tr>
<tr id="row_12_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__RemoveNaNFromPointCloud.html" target="_self">Remove NaN Points from a Point Cloud</a></td><td class="desc">Removes NaN (Not-a-Number) points from an organized point cloud </td></tr>
<tr id="row_13_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__RemoveNaNNormalsFromPointCloud.html" target="_self">Remove NaN Points from a Point Cloud</a></td><td class="desc">Removes points with NaN normal values from a point cloud </td></tr>
<tr id="row_14_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__RadiusFiltering.html" target="_self">Radius Filtering</a></td><td class="desc">Filters points based on the number of neighbors within a given radius </td></tr>
<tr id="row_15_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__ProportionalRadiusFiltering.html" target="_self">Proportional Radius Filtering</a></td><td class="desc">Performs proportional radius outlier filtering using viewpoint-dependent adaptive radii </td></tr>
<tr id="row_16_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__SubtractFiltering.html" target="_self">Subtract Filtering</a></td><td class="desc">Filters a point cloud by removing points that have a sufficient number of neighbors within a given radius in a second point cloud </td></tr>
<tr id="row_17_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__PointNormalFiltering.html" target="_self">Point Normal Filtering</a></td><td class="desc">Filters points in a point cloud based on the angle between their estimated surface normals and a given reference normal </td></tr>
<tr id="row_18_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__ExtractClusters.html" target="_self">Point Cloud Cluster Extraction</a></td><td class="desc">Performs Euclidean cluster extraction on a point cloud </td></tr>
<tr id="row_19_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__ExtractIndices.html" target="_self">Point Cloud Indices Extraction</a></td><td class="desc">Extracts a subset of points from a point cloud based on specified indices </td></tr>
<tr id="row_20_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__ComputeVarianceAndCorrespondences.html" target="_self">Compute Variance and Correspondences of Two Point Clouds</a></td><td class="desc">Computes the geometric variance and number of valid correspondences between two point clouds </td></tr>
<tr id="row_21_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__ComputeNormalsComplexity.html" target="_self">Compute Structural Complexity of a Point Cloud with Normals</a></td><td class="desc">Computes the complexity of surface normals in a point cloud using PCA </td></tr>
<tr id="row_22_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__TransformPointcloud.html" target="_self">Transform PCL Point Clouds</a></td><td class="desc">Transforms various PCL point cloud types using the given transform </td></tr>
<tr id="row_23_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__TransformPoint.html" target="_self">Transform a single point</a></td><td class="desc">Transforms various point types using the given transform </td></tr>
<tr id="row_24_" class="even"><td class="entry"><span style="width:16px;display:inline-block;">&#160;</span><a class="el" href="group__UtiLite.html" target="_self">UtiLite</a></td><td class="desc"></td></tr>
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