teaching:se-kiba:perception-tutorial
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| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| teaching:se-kiba:perception-tutorial [2013/04/26 11:51] – balintbe | teaching:se-kiba:perception-tutorial [2016/05/19 09:19] (current) – external edit 127.0.0.1 | ||
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| Check out the code presented at seminar in your ros-workspace from:\\ | Check out the code presented at seminar in your ros-workspace from:\\ | ||
| - | [[https:// | + | [[https:// |
| Prerecorded bag file can be found in ../ | Prerecorded bag file can be found in ../ | ||
| ==== 2. Viewing and recording data from the Kinect === | ==== 2. Viewing and recording data from the Kinect === | ||
| + | == Bag files and Rviz == | ||
| For a PrimeSense device: connect it to your PC and run: | For a PrimeSense device: connect it to your PC and run: | ||
| roslaunch openni_launch openni.launch | roslaunch openni_launch openni.launch | ||
| Line 32: | Line 32: | ||
| More detail and a more elegant way of saving data from a Kinect to bag files can be found [[http:// | More detail and a more elegant way of saving data from a Kinect to bag files can be found [[http:// | ||
| + | In order to save Point Clouds to *.pcd files run: | ||
| + | rosrun pcl_ros pointcloud_to_pcd / | ||
| + | | ||
| + | == Image_view == | ||
| + | View rgb image: | ||
| + | rosrun image_view image_view image: | ||
| + | View depth image: | ||
| + | rosrun image_view image_view image: | ||
| + | | ||
| + | == From a ROS node == | ||
| + | To see how you subscribe to a topic from a ros node take a look at // | ||
| + | ==== 3.Processing Point Clouds ==== | ||
| - | + | The following are presented in //tutorial.cpp//, for more detailed description check the links attached. | |
| - | * viewing with //rviz// (point clouds) and // | + | * reading in a pcd file[[http:// |
| - | * record using bag files or save clouds in *pcd files using tool in ros_pcl\\ | + | * using PCLVisualizer[[http:// |
| - | * replay bag files, view them in rviz\\ | + | |
| - | * subscribing to the PointCloud topic from C++ | + | |
| - | + | ||
| - | ==Processing Point Clouds== | + | |
| - | + | ||
| - | * reading in a pcd file | + | |
| - | * using PCLVisualizer | + | |
| * removing nans | * removing nans | ||
| - | * filtering based on axes | + | |
| - | * downsampling the Point Cloud | + | |
| - | * RANSAC plane fitting | + | * downsampling the Point Cloud[[http:// |
| - | * extracting indices | + | * RANSAC plane fitting, and extracting indices |
| - | + | For further questions contact: // | |
| - | | + | |
teaching/se-kiba/perception-tutorial.1366977063.txt.gz · Last modified: (external edit)
