Uses of Class PointCloud

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Uses of PointCloud in <Unnamed>

Fields in <Unnamed> declared as PointCloud
Modifier and Type	Field and Description
`(package private) PointCloud`	MeanShiftClustering.`N`
`(package private) PointCloud`	SlowRangeSearch.`N`
`private PointCloud`	MedianWithSorting.`N`
`private PointCloud`	LinearTimeMedian.`N`
`PointCloud`	PointCloud.`next`
`private PointCloud`	KdTree.`points`
`(package private) PointCloud`	MeanShiftClustering.`seeds`

Methods in <Unnamed> that return PointCloud
Modifier and Type	Method and Description
`PointCloud`	MeanShiftClustering.`detectCluster(Jcg.geometry.Point_d seed, int clusterIndex)` Single cluster detection -- returns approximate peak and cluster points The output is a list of point containing: - all the points belonging to the detected cluster - the peak point (at the top of the list)
`PointCloud`	FastRangeSearch.`NN(X q, double sqRad)` Main search procedure (for Range search queries)
`PointCloud`	FastRangeSearch.`OrthogonalRangeSearch(X q, double sqRad)` Perform range search using KdTrees
`PointCloud`	KdTree.`OrthogonalRangeSearch(X q, double sqRad)` Range search: return the list of nearest point to a given query point q.
`PointCloud`	SlowRangeSearch.`OrthogonalRangeSearch(X q, double sqRad)` Linear time search (exhaustive search) Useful for point clouds of small size
`PointCloud`	RangeSearch.`OrthogonalRangeSearch(X q, double sqRad)` Range search: return the list of nearest points to a given query point q.
`static PointCloud`	IO.`pointsFromDataFile(java.lang.String fileName)` Load point clouds from file
`static PointCloud`	IO.`pointsFromImage(java.lang.String imageFile)` Load point clouds from image file
`static PointCloud`	PointCloud.`randomPoints(int n, int dim)` return a point cloud of n random points (in the unit hyper-square in dimension dim)
`static PointCloud`	PointCloud.`randomPointsOnCircle(int n, int dim)` return a point cloud of n random points sampled on a circle (according to normal distribution)
`static PointCloud`	ImageManipulation.`rasterToPointCloud(java.awt.image.Raster r, int dimx, int dimy, int dim)`
`static PointCloud[]`	KdTree.`split(PointCloud N, double cutValue, int cutDim)` Split a point cloud into two sub-point clouds (lower an upper point clouds)

Methods in <Unnamed> with parameters of type PointCloud
Modifier and Type	Method and Description
`static double[]`	PointCloud.`boundingBox(PointCloud N)`
`static <X extends Jcg.geometry.Point_> KdTree<X>`	KdTree.`constructDataStructure(PointCloud N, int pDim)` Construct a Kd-Tree from a point cloud (in dimension pDim)
`static Jcg.geometry.Point_d[]`	PointCloud.`copy(PointCloud N, int size)`
`static void`	Draw.`draw2D(PointCloud N, java.lang.String title)` Draw a point cloud in a 2D frame (using x and y coordinates)
`static void`	Draw.`draw3D(PointCloud N)` Draw a point cloud in a 3D frame (with no colors)
`static void`	Draw.`draw3D(PointCloud N, Cluster<Jcg.geometry.Point_d> cluster)` Draw a point cloud in 3D with colors.
`static void`	Draw.`draw3D(PointCloud N, java.awt.Color[] colors)`
`static void`	Draw.`draw3DNColors(PointCloud N)` Draw a point cloud in a 3D frame (with no colors)
`(package private) void`	MeanShiftClustering.`initMSC(PointCloud n, PointCloud s, double cr, double ar, double ir, double mr)`
`static Jcg.geometry.Point_d`	PointCloud.`mean(PointCloud N)`
`int`	MeanShiftClustering.`mergeCluster(PointCloud cluster, Jcg.geometry.Point_d[] clusterCenters)` Perform cluster merging Remark: cluster center is at top of cluster cloud
`static void`	ImageManipulation.`PointCloudToRaster(PointCloud n, Cluster<Jcg.geometry.Point_d> cluster, java.awt.Color[] cols, java.awt.image.WritableRaster r, int dimx, int dimy, int dim)`
`static int`	PointCloud.`size(PointCloud N)` return the size (number of points)
`static PointCloud[]`	KdTree.`split(PointCloud N, double cutValue, int cutDim)` Split a point cloud into two sub-point clouds (lower an upper point clouds)
`static void`	TestKdTree.`testConstructionKdTree(PointCloud N)`
`static void`	TestMeanShift.`testDetectCluster(PointCloud N, double bandwidth)`
`static void`	TestMeanShift.`testMeanShift(PointCloud N, double bandwidth)`
`static void`	TestMedian.`testMedianComputing(PointCloud N)`

Constructors in <Unnamed> with parameters of type PointCloud
Constructor and Description
`FastRangeSearch(PointCloud N)` Construct the data structure for range search
`KdTree(PointCloud N, int pDim, int cutDim)` Constructor -- builds the entire Kd-tree at once recursively
`LinearTimeMedian(PointCloud points)`
`MeanShiftClustering(PointCloud n, double bandWidth)`
`MeanShiftClustering(PointCloud n, PointCloud s, double cr, double ar, double ir, double mr)`
`MedianWithSorting(PointCloud points)`
`PointCloud(Jcg.geometry.Point_d p, PointCloud n, boolean copy)` Constructor: add a new point to the cloud (copying or not)
`SlowRangeSearch(PointCloud N)`

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