Robotics Class 2011/Assignment 2
Write a ROS node that subscribes to the image topic "/stereo/left/image_rect" (which has message type sensor_msgs/Image), and publish two topics. The first topic is a topic named "/face_view" that is an image topic that has a rectangle around any face that is seen. The second topic, named "/face_coords" is a PointStamped message that has point.x and point.y set to the center of the identified face if there is one face. If there is more than one face, the behavior can be implementation dependent.
In class we discussed some basic properties of a mathematical model of the pinhole camera, which in turn provided insights into the idea of camera calibration and image rectification. Camera calibration is discussed in detail in the OpenCV Camera Calibration Section.
To start the assignment, you can learn about the structure of the PointStamped message by typing:
rosmsg show PointStamped
Remember when working at home to comment out the two lines in your .bashrc file that contain ROS_IP and ROS_MASTER_URI definitions for working with the robot at the HacDC space. Once you have commented out those two lines (and have restarted your shell or sourced your .bashrc), make sure also to start your own local roscore (the ROS master node) by typing:
The bag file distributed in class contains the image data that should be used to test your face detector. You can download the bag file here. The bag file can be played back by typing:
rosbag play -l 2011-06-18-12-38-55.bag
Note that the additional "-l" argument allows the bag file to be looped indefinitely.
Once the bag file has begun playing, you can verify the image stream by viewing the raw images from the bag file by typing:
rosrun image_view image_view image:=/stereo/left/image_rect
Once the image stream is verified to be working, you can begin developing your face detection system.
There is a complete example of the homework in the HacDC ROS repository. If you would like to refer to it, you can check it out via:
cd to where you store your downloaded ROS packages
Note that the homework solution uses cv_bridge to map between ROS image messages and OpenCV image arrays, and it makes use of the OpenCV image blurring function cv.Smooth and face detection function cv.HaarDetectObjects.
In order to actually run the demonstration face detector, you will need to use the roslaunch tool. When you check out the above face_detection module from the HacDC repository, you will find inside the package a directory named launch. Inside this directory is a ROS launch file designed to start up the face detection module. The roslaunch system is useful for starting up a large number of nodes on your robot, instead of manually starting each node in a separate window using rosrun.... Inside the (XML) launch file we also define a "private" parameter that is loaded to the ROS Parameter Server. As mentioned in class, this parameter is named "classifier" and it contains the filename to the Haar Cascade used by the OpenCV face detection algorithm.
In order to start the face detection example node, you may type:
roslaunch face_detection face_detector.launch
As the assignment requests, the example face_detector node outputs two topics, one called "/face_view" and one called "/face_coords". You can view the "/face_view" image topic like you would any other image topic (using image_view):
rosrun image_view image_view image:=/face_view
If you wish to view the "/face_coords" topic, you made use the simple rostopic echo covered previously:
rostopic echo /face_coords
Note that the "/face_coords" topic is only transmitted (in the face detection example node at least) when faces are detected.