Rdiankov: Created page with "= Object Detection with ROS/OpenRAVE = "posedetection_msgs", which decides the connection message, is the central role here. Each feature and obj..."

2011-04-18T15:08:18Z

Created page with "= Object Detection with ROS/OpenRAVE = "posedetection_msgs", which decides the connection message, is the central role here. Each feature and obj..."

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= Object Detection with ROS/OpenRAVE =

"posedetection_msgs", which decides the connection message, is the central role here. Each feature and object-detection module use this message, and therefore they can cooperate with one another.

Message F
Curve1D
Feature0D
Feature1D
ImageFeature0D
ImageFeature1D
Object6DPose - One detected object
ObjectDetection - Object detection output
Service F
Detect
Feature0DDetect
Feature1DDetect

Features are separated between 0-dimensional "point" and 1-dimensional "line".

The package required to compute features according to this message is
imagesift

The package required to output the result of the object according to this message is
checkerboard_detector
posedetectiondb

= Posture-and-orientation detection of textured planes =

Let's boot up the easy program on plane detection based on PointPoseExtraction.py script in posedetectiondb

rosmake --rosdep-install posedetectiondb

== Quick start ==

To start feature extraction F
rosrun imagesift imagesift

To start detection module
rosrun posedetectiondb PointPoseExtraction.py

Choose 4 points by left click on the mouse, and create template.pp file. This texture is used to be searched from images.

To see the image in pp file, run the following script
python -c "import scipy, pickle; scipy.misc.pilutil.imshow(pickle.load(open(raw_input('enter filename: '),'r'))['Itemplate'])"

==Execution example using IEEE1394Camera(FLEA)==
Open camera F
The example of roslaunch file is as follows
<source lang="xml">
<launch>
<group ns="FLEA">
<param name="display" type="int" value="0"/>
<param name="mode" value="MODE_640x480_MONO8"/>
<param name="framerate" type="double" value="15"/>
<param name="colorfilter" type="string" value="COLOR_FILTER_GBRG"/>
<param name="compression" type="string" value="raw"/>
<param name="frame_id" type="string" value="left_base"/>
<param name="KK_fx" type="double" value="493.336823"/>
<param name="KK_fy" type="double" value="493.239960"/>
<param name="KK_cx" type="double" value="308.050354"/>
<param name="KK_cy" type="double" value="242.917526"/>
<param name="kc_k1" type="double" value="-0.342432"/>
<param name="kc_k2" type="double" value="0.123768"/>
<param name="kc_p1" type="double" value="-0.000268"/>
<param name="kc_p2" type="double" value="0.000052"/>
<node name="cam" pkg="cameradc1394" type="cameradc1394" respawn="true" output="screen">
</node>
<node name="iview" pkg="image_view" type="image_view">
</node>
</group>
</launch>
</source>
sudo chown user:group /dev/raw1394
roslaunch cameradc.ros.xml

The explanation of calib is in
http://openrave.programmingvision.com/index.php/Working_with_Cameras

Start feature extraction F

ROS_NAMESPACE=FLEA rosrun imagesift imagesift
Of course it is also possible to roslaunch as follows
<source lang="xml">
<launch>
<group ns="FLEA">
<node name="sift" pkg="imagesift" type="imagesift" output="screen"/>
</group>
</launch>
</source>

Start detection module and create template.pp F
ROS_NAMESPACE=FLEA rosrun posedetectiondb PointPoseExtraction.py
Click the four corners of the detection-target texture one by one.

[[image:ttest1.png|300px]]
[[image:ttest2.png|300px]]
[[image:ttest3.png|300px]]
[[image:ttest4.png|300px]]

The vector from the first point to the second point becomes the positive sense of x-axis.

In the current specification, to click points clockwise is expected.

(The above image was captured before bug fixing. I will replace it by a new one someday.)

When you finish clicking the fourth point, you will be asked to input the width and height on the terminal.
Input them in the order of "width height", by meters.

(For example, input "0.13 0.14" if the size is 13cmx14cm.)

If it is suceeded, the following window appears

[[image:ttest5.png|300px]]

P.S.: Fatal bug, which brought a mirror plane as above, was fixed on 5/3.
The detection accuracy increased dramatically.
I will replace the above image by a new one someday.

Detection test F
The example of roslaunch file is as follows
<source lang="xml">
<launch>
<group ns="FLEA">
<node name="template" pkg="posedetectiondb"
type="PointPoseExtraction.py" args="--errorthresh=0.007
--neighthresh=0.8 --dminexpected=10 --ransaciters=200
--template=/hoge/template.pp" output="screen"/>
</group>
</launch>
</source>
The parameters are only an example.

Running camera and imagesift, roslaunch this
roslaunch template.ros.xml

The success examples are as follows

[[image:ttest6.png|300px]]
[[image:ttest7.png|300px]]

== Explanation of parameters ==
rosrun posedetectiondb PointPoseExtraction.py --help
When you run this script, you can see the explanation of each parameter.

== Connection to OpenRAVE Objects ==

ROS:Object Detection - Revision history

Rdiankov: Created page with "= Object Detection with ROS/OpenRAVE = "posedetection_msgs", which decides the connection message, is the central role here. Each feature and obj..."