FiducialDetector plugins

Classes
struct	icl::markers::FiducialDetectorPlugin
	Generic Interface class for FiducialDetector plugins. More...
class	icl::markers::FiducialDetectorPluginAmoeba
	FiducialDetectorPlugin for reacTIVision's 'amoeba' markers. More...
class	icl::markers::FiducialDetectorPluginART
	FiducialDetectorPlugin for ARToolkit like markers using binary image patches as marker IDs. More...
class	icl::markers::FiducialDetectorPluginBCH
	FiducialDetectorPlugin for ARToolkit+ like markers using BCH coded IDs. More...
class	icl::markers::FiducialDetectorPluginForQuads
	FiducialDetectorPlugin for quad-markers like ARToolkit and BCH-Code markers. More...
class	icl::markers::FiducialDetectorPluginHierarchical
	Extra abstraction layer that defines a basic skeleton for the detection of hierarchical fiducials. More...
class	icl::markers::FiducialDetectorPluginICL1
	FiducialDetectorPlugin for ARToolkit+ like markers using BCH coded IDs. More...

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Detailed Description

The ICLMarkers package defines general interfaces for most different types of marker detection methods. The essential classes of this package are

• icl::markers::FiducialDetector (for detection different types of markers in images)
• icl::markers::Fiduical (a list of instances of this type is returned by the fiducial detection step

Note: We use the words "fiducial" and "marker" or "image marker" as synonyms.

The FiducialDetector implements a plugin-based system which can be configured at instantiation type in order to use a certain marker detection backend. Dependent on the selected backend, the detection markers (of type icl::Fiducial) provide a different set of information -- some can only provide 2D information, others do also provide 3D pose information. Also dependent on the chosen plugin type, markers have to be loaded in a certain way that is also generalized by single method FiducialDetector::loadMarkers.

Speed

Internally, most detection steps are optimized for beeing fast on large images (>= VGA resolution),i.e. usually the plugins try to get away from the pixel representation by switching to binarized image regions. Benchmarks for different types of input image sizes and marker types are given in the Benchmarks section

Supported Marker Types

"art" marker	"bch" marker	"amoeba" marker	"icl1" marker

• "art"
  for ARToolkit markers (visit the ARToolkit Webpage for more details) ART Fiducials can provide the full set of information including the 3D pose from a single marker
• "bch"
  for ARToolkit+/Studierstube-Tracker like bch-code based binary markers (visit the Studierstube Tracker Homepage for more details) BCH Fiducials can provide the full set of information including the 3D pose from a single marker. Usually, the detection rate is faster and more accurate in comparison to artoolkit markers.
• "amoeba" }
  for The amoeba style hierarchical markers provided by the reactivision software Amoeba fiducials cannot be detected in 3D. They do only provide 2D center and rotation and the 2D boundary.
• "icl1"
  for ICL's former 'paper' markers. These markers consist of 4 vertical sections. Each of these sections contains a number of dot-regions. Therefore, the marker detection method is comparable to other hierarchical markers such as "amoeba", however, the well defined marker structure allows for the systematic identification of every single marker region, which provides better 3D pose-estimation results.

Benchmarks

TODO

Multithreading

We did not speed up the algorithms using multithreading techniques since usually the provided methods are fast enough using a single thread. "Fast enough" means, that the detection is faster than the amount of data, that is usually provided by common cameras. Perhaps, multithreading will added later as a 'utils::Configurable' property.

Example

#include <ICLQt/Common.h>
#include <ICLMarkers/FiducialDetector.h>

// static application data
HSplit hsplit;
GUI gui(hsplit);
GenericGrabber grabber;

// the global detector class
// here, using the first 100 "bch"-markers
icl::markers::FiducialDetector fid("bch","[0-100]","size=30x30");

// initialization function (called once after start)
void init(){
  // the the configurable ID
  fid.setConfigurableID("fid");

  // create the GUI
  gui << Draw().handle("draw")        // create drawing component
      << Prop("fid").maxSize(18,100)  // create the propery widged for 'fid'
      << Show();                      // show the main widget

  // initialize the grabber from given program argument
  grabber.init(pa("-input"));
}


// working loop (automatically looped in the working thread)
void run(){
  // get a handle to the "draw" component
  static DrawHandle draw = gui["draw"];

  // grab the next image
  const core::ImgBase *image = grabber.grab();

  // detect markers
  const std::vector<Fiducial> &fids = fid.detect(image);

  // visualize the image
  draw = image;

  // draw marker detection results
  draw->linewidth(2);
  for(unsigned int i=0;i<fids.size();++i){
    utils::Point32f c = fids[i].getCenter2D();
    float rot = fids[i].getRotation2D();

    draw->color(0,100,255,255);
    draw->text(fids[i].getName(),c.x,c.y,10);
    draw->color(0,255,0,255);
    draw->line(c,c+utils::Point32f( cos(rot), sin(rot))*100 );

    draw->color(255,0,0,255);
    draw->linestrip(fids[i].getCorners2D());

  }
  // update the visualization
  draw.render();
}

// main method
int main(int n, char **ppc){
  return ICLApp(n,ppc,"[m]-input|-i(2)",init,run).exec();
}