Constructor Detail

• ICP

  public ICP(List<P> target,
             List<P> reference,
             PointMatchIdentification<P> pointMatchIdentifier)

  Instantiates a new ICP object with the List of target and reference points as well as the PointMatchIdentification interface that defines how corresponding points are identified.
  Note that the elements of the Lists have to implement Point(for compatibility with Model) and Leaf(for compatibility with KDTree).

  Parameters:

  target - - the List of target points

  reference - - the List of reference points

  pointMatchIdentifier - - the PointMatchIdentification which defines how correspondences are established

• ICP

  public ICP(List<P> target,
             List<P> reference,
             double distanceThreshold)

  Also instantiates a new ICP instance, but uses the SimplePointMatchIdentification to define corresponding points.

  Parameters:

  target - - the List of target points

  reference - - the List of reference points

  distanceThreshold - - the maximal distance of SimplePointMatchIdentification, so that the nearest neighbor of a point is still counted as a corresponding point

• ICP

  public ICP(List<P> target,
             List<P> reference)

  Also instantiates a new ICP instance, but uses the SimplePointMatchIdentification to define corresponding points.

  Parameters:

  target - - the List of target points

  reference - - the List of reference points

Method Detail

• runICPIteration

  public void runICPIteration(Model<?> lastModel,
                              Model<?> newModel)
                       throws NotEnoughDataPointsException,
                              IllDefinedDataPointsException,
                              NoSuitablePointsException

  Performs one iteration of the ICP. It takes the last Model as input to find the corresponding points for the new Model. The result is the new Model, the number of corresponding points, the average, and the maximal error. Note that lastModel and newModel can be the same instance and it will be overwritten.

  Parameters:

  lastModel - - The last Model that maps the target.local coordinates to the reference.world coordinates, used to find the corresponding points

  newModel - - The Model that maps the target.local coordinates to the reference.world coordinates, will be fitted to the new points

  Throws:

  NotEnoughDataPointsException

  IllDefinedDataPointsException

  NoSuitablePointsException

• estimateIntialModel

  public void estimateIntialModel(List<PointMatch> matches,
                                  Model<?> model)
                           throws NotEnoughDataPointsException,
                                  IllDefinedDataPointsException

  Estimates an initial Model based on some given PointMatches. Note that the PointMatches have to be stored as PointMatch(target,reference).

  Parameters:

  matches - - The List of apriori known PointMatches

  model - - The Model to use

  Throws:

  NotEnoughDataPointsException

  IllDefinedDataPointsException

• setPointMatchIdentification

  public void setPointMatchIdentification(PointMatchIdentification<P> pointMatchIdentifier)

  Sets the PointMatchIdentification that defines how PointMatches between reference and target are identified. The simplest way to do it is the SimplePointMatchIdentification class which takes the nearest neighbor with a minimal distance threshold.

  Parameters:

  pointMatchIdentifier - - the new PointMatchIdentification

• getPointMatchIdentification

  public PointMatchIdentification<P> getPointMatchIdentification()

  Returns the current PointMatchIdentification that is used to identfy corresponding points

  Returns:

  PointMatchIdentification> P <

• getPointMatches

  public List<PointMatch> getPointMatches()

  Return the List of PointMatches (target, reference) of the last ICP iteration

  Returns:

  - List of PointMatches

• getAverageError

  public double getAverageError()

  Returns the average error of the last ICP iteration, or -1 if no iteration has been computed yet.

  Returns:

  double - average error

• getMaximalError

  public double getMaximalError()

  Returns the maximum error of a PointMatch of the last ICP iteration, or -1 if no iteration has been computed yet.

  Returns:

  double - maximal error

• getNumPointMatches

  public int getNumPointMatches()

  Returns the number of PointMatches of the last ICP iteration, or -1 if no iteration has been computed yet.

  Returns:

  int - number of PointMatches

• getNumAmbigousMatches

  public int getNumAmbigousMatches()

  Returns the number of ambigous PointMatches indentified in the last ICP iteration, or -1 if no iteration has been computed yet.

  Returns:

  int - number of ambigous PointMatches

• getAmbigousMatches

  public ArrayList<PointMatch> getAmbigousMatches()

  Returns the ArrayList of ambigous PointMatches indentified in the last ICP iteration, or null if no iteration has been computed yet.

  Returns:

  int - ArrayList of PointMatches

• getTargetPoints

  public List<P> getTargetPoints()

• getReferencePoints

  public List<P> getReferencePoints()

• removeAmbigousMatches

  public static ArrayList<PointMatch> removeAmbigousMatches(List<PointMatch> matches)

  Detects ambigous (and duplicate) PointMatches, i.e. if a Point corresponds with more than one other Point

  Parameters:

  matches - - the List of PointMatches

  Returns:

  - the ArrayList containing the removed ambigous or duplicate PointMatches

• getOccurences

  protected static ArrayList<Integer> getOccurences(Point pointTarget,
                                                    Point pointReference,
                                                    List<PointMatch> list)

  Computes if one Point pair occurs more than once in a List of PointMatches

  Parameters:

  pointTarget - - one Point

  pointReference - - the other Point

  list - - the List of PointMatches (target, reference)

  Returns:

  - an ArrayList of indices which should be removed due to duplicate or ambigous occurence