3D ball tracker
This page contains information on how to build, set up and run pf3dTracker, the particle-filter-based 3D ball tracker, and pf3dBottomup, the 3D ball detector. The page is in the process of being written, so it's incomplete and the information you find on it might be inaccurate. Should you have any question or complaint, please write Matteo Taiana an email at: mtaiana at isr*ist*utl*pt. The algorithm of the tracker is described in the paper: "Tracking objects with generic calibrated sensors: an algorithm based on color and 3D shape features", please cite it if you use the tracker in your research.
System architecture and behaviour
The two modules work as depicted in the following image: the bottom up module detects balls in the input images and sends 3D hypotheses on the position of balls to the tracker. Using the two modules together enables the usual robust tracking plus fast detection. Should you have any reason for that, the tracker can be run on its own.
For the two modules to work well together, they should share the same colour and shape model for the ball, and the same camera model parameters. See |below for details on how to write the initialization files accordingly.
Get and build the source code
The source code of tracker and detector is part of the iCub repository, this page explains how to get it, this other one how to build it. Both modules depend on YARP and OpenCV, the tracker depends also on iKin, while the bottom up module depends also on iCubVis. On this page you will encounter the variables $ICUB_ROOT and $ICUB_DIR. $ICUB_ROOT should point to the root of your copy of the iCub repository, while $ICUB_DIR should point to the directory where you build or install the binaries, have a look here for more information. The source code of the tracker is contained in the directory: $ICUB_ROOT/main/src/modules/pf3dTracker, the one for the detector is in: $ICUB_ROOT/main/src/modules/pf3dBottomup. The binaries, after the building process, are stored in the directory: $ICUB_DIR/bin. You should be able to invoke them from any directory.
Configuration
Configure the tracker
An example configuration comes with the iCub software, so you can test the tracker even without creating the models which are presented hereafter. Beware that the tracker will not work well without customized models.
For the tracker to work properly, you need to create a colour model for the specific ball you want to track. This is done by grabbing images with the camera you want to use, cutting out the parts of the images where the ball is seen and pasting them all together in one file. The background of this image should be white, as white pixels are discarded when building the model histogram. The robustness of the tracker will depend on this model: you should include images in which the ball is seen under different lighting conditions. The more images you cut out, the better. If you can change the colour/brightness parameters of the camera, please do so before creating the colour model and use the same settings every time you use the tracker. Good setting include high saturation and a brightness that never makes parts of the ball appear as white or black.
Two examples of colour template images, for a yellow and a red ball, respectively:
Some images depicting the hand of the iCub robot were included in the template for the red ball, hoping this will improve the tracking when the ball is partially occluded by the hand of the robot.
You need to create a shape model for the specific ball you want to track. This is done using the Matlab script $ICUB_ROOT/main/src/modules/pf3dTracker/matlab_files/write_initial_ball_points.m. You should set three parameters inside the script: R, R1 and R2. R is the radius of the ball you want to track, in millimetres. R1 and R2 are the radii that are used to project the inner and outer contour (see [[1]] for more details). If you want a precise estimate of the 3D position of the ball, you should set R1 and R2 close to the value of R (e.g. 10% difference). If you want the tracker to be able to withstand high accelerations of the ball, maintaining the number of particles used low, you should increase the difference up to 30% (this is the value I typically use). This script will create a file called something like: initial_ball_points_31mm_30percent.csv.
You need to create a dynamic model for the ball. Basically you have to fill in the dynamic matrix. I use a constant velocity model, with random acceleration. The data for this is stored in: models/motion_model_matrix.csv. I'm not sure that the tracker will work properly with other configurations of the motion model. For the dynamic model it is also quite important the parameter AccelStDev, that is set in the initialization file (see below).
You need to calibrate the camera you use i.e. estimate the intrinsic camera parameters. You can do that using camCalibConf, for example.
You need to customize the file that sets the tracker up on start up. The default initialization file is $ICUB_ROOT/main/app/pf3dTracker/conf/pf3dTracker.ini. Here is an example:
#################################### #configuration file for pf3dTracker# #################################### ############# #module name# ############# name /pf3dTracker ############################# #parameters of the algorithm# ############################# nParticles 900 #nParticles number of particles used accelStDev 30 #accelStDev standard deviation of the acceleration noise insideOutsideDiffWeight 1.5 #insideOutsideDiffWeight inside-outside difference weight for the likelihood function colorTransfPolicy 1 #colorTransfPolicy [0=transform the whole image | 1=only transform the pixels you need] ######################### #port names and function# ######################### inputVideoPort /pf3dTracker/video:i #inputVideoPort receives images from the grabber or the rectifying program. outputVideoPort /pf3dTracker/video:o #outputVideoPort produces images in which the contour of the estimated ball is highlighted. outputDataPort /pf3dTracker/data:o #outputDataPort produces a stream of data in the format: X, Y, Z [meters], likelihood, U, V [pixels], seeing_object. inputParticlePort /pf3dTracker/particles:i #inputParticlePort receives hypotheses on the position of the ball from the bottom up module outputParticlePort /pf3dTracker/particles:o #outputParticlePort produces data for the plotter. it is usually not active for performance reasons. outputAttentionPort /pf3dTracker/attention:o #outputAttentionPort produces data for the attention system, in terms of a peak of saliency. ################################# #projection model and parameters# ################################# #projectionModel [perspective|equidistance|unified] projectionModel perspective #iCubLisboaLeftEye_Zoom_Lens_2009_05_19 w 320 h 240 perspectiveFx 445.202 perspectiveFy 445.664 perspectiveCx 188.297 perspectiveCy 138.496 ####################### #tracked object models# ####################### #trackedObjectType [sphere|parallelogram] trackedObjectType sphere trackedObjectColorTemplate models/red_smiley_2009_07_02.bmp trackedObjectShapeTemplate models/initial_ball_points_smiley_31mm_20percent.csv motionModelMatrix models/motion_model_matrix.csv trackedObjectTemp current_histogram.csv ####################### #initialization method# ####################### #initialization method [search|3dEstimate|2dEstimate] initializationMethod 3dEstimate #initial position [meters] initialX 0 initialY 0 initialZ 0.5 #################### #visualization mode# #################### #circleVisualizationMode [0=inner and outer circle | 1=one circle with the correct radius] #default 0. only applies to the sphere. circleVisualizationMode 1 ######################### #attention-related stuff# ######################### #the tracker produces a value of likelihood at each time step. #this value can be used to infer if the object it is tracking is the correct one. #this is not a very robust way of doing so. #if likelihood>this value, then probably I'm tracking the object. likelihoodThreshold 0.005 attentionOutputMax 300 attentionOutputDecrease 0.99 ########################## #image saving preferences# ########################## #save images with OpenCV? saveImagesWithOpencv false #always use the trailing slash here. saveImagesWithOpencvDir ./graphical_results/
Configure the bottom up module
The default initialization file for configuring the detector is $ICUB_ROOT/main/app/pf3dBottomup/conf/pf3dBottomup.ini. Here is an example:
nParticles 50 #number of generated particles maskVmin 15 #minimum acceptable pixel value maskVmax 256 #maximum acceptable pixel value maskSmin 70 #minimum acceptable pixel saturation Blur 1 #gaussian blur variance #ball shape (size) model sphereRadius 0.031 #radius of the ball in meters #ball colour model file trackedObjectColorTemplate models/red_smiley_2009_07_02.bmp #projection model parameters: w 320 h 240 perspectiveFx 445.202 perspectiveFy 445.664 perspectiveCx 188.297 perspectiveCy 138.496
Configuring the modules to work well together
You should make sure that the two modules use the same colour model for the ball, i.e., the parameter "trackedObjectColorTemplate", in the two initialization files, should point to the same file. A simple way of doing so is by putting a copy of the same file in both conf/models directories ($ICUB_ROOT/main/app/pf3dTracker/conf/models/ and $ICUB_ROOT/main/app/pf3dBottomup/conf/models/) and having the initialization files pointing at them:
Initialization file for the tracker:
trackedObjectColorTemplate models/red_smiley_2009_07_02.bmp
Initialization file for the detector:
trackedObjectColorTemplate models/red_smiley_2009_07_02.bmp
You should make sure that the projection model parameters are the same:
w 320 h 240 perspectiveFx 445.202 perspectiveFy 445.664 perspectiveCx 188.297 perspectiveCy 138.496
You should make sure that the size of the tracked ball is the same for both modules. In the initialization file for the tracker, you find the line:
trackedObjectShapeTemplate models/initial_ball_points_smiley_31mm_20percent.csv
which implies that the radius of the ball is 31mm. This should be matched by the following line in the initialization file for the detector:
sphereRadius 0.031 #radius of the ball in meters
Run the tracker
The tracker works best if the brightness/colour parameters of the camera are set at the same values they had at the time of the acquisition of the images that form the colour model. To make sure of this, you should note down the values of the camera parameters at the time of the acquisition of such images and set the parameters again to those values before running the tracker (you can use frameGrabberGui for this).
Here is an example of such parameters:
brightness 0 sharpness 0.5 white balance 0.648 0.474 hue 0.482 saturation 0.826 gamma 0.400 shutter 0.592 gain 0.305
Run the tracker via the application manager
You need to change the "node" information in the xml file before you run it. This script relies on yarprun. If you do not know what yarprun is, it's probably faster if you try the other method to run the tracker.
cd $ICUB_ROOT/app/default/scripts ./manager.py $ICUB_ROOT/app/demoReach_IIT_ISR/scripts/iit/demoReach_IIT_ISR_NoHand.xml
or
cd $ICUB_ROOT/app/default/scripts ./manager.py $ICUB_ROOT/app/demoReach_IIT_ISR/scripts/isr/demoReach_IIT_ISR_JustTracker.xml
To run the tracker together with the bottom up detection module:
cd $ICUB_ROOT/app/pf3dTracker/scripts manager.py pf3dTrackerWithBottomup.xml
Check the dependencies, run the modules and connect the ports.
Run the tracker invoking commands from the shell
#run an image rectifier, in case you need it (cameras with a non-negligible distortion) camCalib --file iCubLeftEye.ini --name /icub/camcalib/left #run the tracker itself pf3dTracker #start a viewer yarpview /viewer #connect all the ports yarp connect /icub/cam/left /icub/camcalib/left/in yarp connect /icub/camcalib/left/out /pf3dTracker/video:i yarp connect /pf3dTracker/video:o /viewer
You can specify a context and an initialization file name for the tracker with the options --context and --from. For more information on this matter, please check out these pages on the resource finder: [2], [3].
Theoretical foundations of the tracker
If you want to know more on the theoretical ideas behind the tracker, please have a look at the papers on this page: [4].
Demo videos
If you want to watch videos and evaluate the performance of the tracker, please have a look at this page: [5].
ToDo
Translate from Matlab to C++ the piece of code that computes the initial ball points and read the value of the radius from the initialization file- Read the color/illumination parameters from the camera before starting the tracker; set the desired parameters of the camera, then start the tracker; restore the original parameters when quitting
- Make the tracker compute the histogram with Gaussian kernels instead of Dirac's
- Make the tracker quit gracefully when asked to, instead of requiring multiple ctrl-c's
- Document the code with Doxygen
- Add the "Expected behaviour" section to the wiki, where the desired behaviour of the tracker is described.
Make the tracker adaptive to different image sizes- Turn the number of particles into a parameter loaded at start time
- Get rid of IPP dependency, using OpenCV
