diff --git a/doc/tutorials/content/interactive_icp.rst b/doc/tutorials/content/interactive_icp.rst index f2c41cb5aee..7d997509b03 100644 --- a/doc/tutorials/content/interactive_icp.rst +++ b/doc/tutorials/content/interactive_icp.rst @@ -29,7 +29,7 @@ Subdivide the original mesh to make it more dense : .. image:: images/interactive_icp/add_sub.png :height: 500 -Configure the subdivision to 2 or 3 for example : dont forget to apply the modifier +Configure the subdivision to 2 or 3 for example : don't forget to apply the modifier .. image:: images/interactive_icp/sub2.png :height: 203 @@ -73,7 +73,7 @@ The bool will help us know when the user asks for the next iteration of ICP :language: cpp :lines: 14-24 -This functions takes the reference of a 4x4 matrix and prints the rigid transformation in an human +This function takes the reference of a 4x4 matrix and prints the rigid transformation in an human readable way. .. literalinclude:: sources/interactive_icp/interactive_icp.cpp @@ -182,7 +182,7 @@ and we set max iterations to 1 in lines 90-93. As before we check if ICP as converged, if not we exit the program. **printf("\033[11A");** is a little trick to go up 11 lines in the terminal to write over the last matrix displayed. In short it allows to replace text instead of writing -new lines; making the ouptut more readable. +new lines; making the output more readable. We increment **iterations** to update the text value in the visualizer. Now we want to display the rigid transformation from the original transformed point cloud to diff --git a/doc/tutorials/content/normal_estimation.rst b/doc/tutorials/content/normal_estimation.rst index ec8dd2879ec..96d572c01a0 100644 --- a/doc/tutorials/content/normal_estimation.rst +++ b/doc/tutorials/content/normal_estimation.rst @@ -144,7 +144,7 @@ representation. To better illustrate this issue, the figure below presents the effects of selecting a smaller scale (i.e., small **r** or **k**) versus a larger scale (i.e., large **r** or **k**). The left part of the figures depicts a reasonable well chosen scale factor, with estimated surface normals -approximatively perpendicular for the two planar surfaces and small edges +approximately perpendicular for the two planar surfaces and small edges visible all across the table. If the scale factor however is too big (right part), and thus the set of neighbors is larger covering points from adjacent surfaces, the estimated point feature representations get distorted, with diff --git a/doc/tutorials/content/octree.rst b/doc/tutorials/content/octree.rst index 2933b89f676..f38adfdcd84 100644 --- a/doc/tutorials/content/octree.rst +++ b/doc/tutorials/content/octree.rst @@ -30,7 +30,7 @@ We fist define and instantiate a shared PointCloud structure and fill it with ra Then we create an octree instance which is initialized with its resolution. This octree keeps a vector of point indices within its leaf nodes. -The resolution parameter describes the length of the smalles voxels at lowest octree level. The depth of the octree is therefore a function of the resolution as well as +The resolution parameter describes the length of the smallest voxels at lowest octree level. The depth of the octree is therefore a function of the resolution as well as the spatial dimension of the pointcloud. If a bounding box of the pointcloud is know, it should be assigned to the octree by using the defineBoundingBox method. Then we assign a pointer to the PointCloud and add all points to the octree. diff --git a/doc/tutorials/content/using_pcl_pcl_config.rst b/doc/tutorials/content/using_pcl_pcl_config.rst index f6271ba672a..7c16b68df29 100644 --- a/doc/tutorials/content/using_pcl_pcl_config.rst +++ b/doc/tutorials/content/using_pcl_pcl_config.rst @@ -103,7 +103,7 @@ The executable we are building makes call to PCL functions. So far, we have only included the PCL headers so the compilers knows about the methods we are calling. We need also to make the linker knows about the libraries we are linking against. As said before the, PCL -found libraries are refered to using ``PCL_LIBRARIES`` variable, all +found libraries are referred to using ``PCL_LIBRARIES`` variable, all that remains is to trigger the link operation which we do calling ``target_link_libraries()`` macro. PCLConfig.cmake uses a CMake special feature named `EXPORT` which diff --git a/doc/tutorials/content/vfh_estimation.rst b/doc/tutorials/content/vfh_estimation.rst index 5a079c654c4..734d2b2d47f 100644 --- a/doc/tutorials/content/vfh_estimation.rst +++ b/doc/tutorials/content/vfh_estimation.rst @@ -112,7 +112,7 @@ Visualizing VFH signatures -------------------------- *libpcl_visualization* contains a special **PCLHistogramVisualization** class, -which is also used by **pcl_viewer** to automaticall display the VFH +which is also used by **pcl_viewer** to automatically display the VFH descriptors as a histogram of float values. For more information, please see http://www.pointclouds.org/documentation/overview/visualization.php. diff --git a/doc/tutorials/content/vfh_recognition.rst b/doc/tutorials/content/vfh_recognition.rst index a248a9ea809..41b9b626c09 100644 --- a/doc/tutorials/content/vfh_recognition.rst +++ b/doc/tutorials/content/vfh_recognition.rst @@ -75,7 +75,7 @@ below: .. image:: images/vfh_recognition/scene_segmented.jpg -Since we're only trying to cover the explicity training/testing of VFH +Since we're only trying to cover the explicit training/testing of VFH signatures in this tutorial, we provide a set of datasets already collected at: `vfh_recognition_tutorial_data.tbz `_.