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Searches feature tree for k nearest neighbors of given reference points.

Namespace: Emgu.CV
Assembly: Emgu.CV (in Emgu.CV.dll) Version: 2.4.10.1935 (2.4.10.1935)

Syntax

C#
public static void cvFindFeatures(
	IntPtr tr,
	IntPtr desc,
	IntPtr results,
	IntPtr dist,
	int k,
	int emax
)
Visual Basic
Public Shared Sub cvFindFeatures ( 
	tr As IntPtr,
	desc As IntPtr,
	results As IntPtr,
	dist As IntPtr,
	k As Integer,
	emax As Integer
)
Visual C++
public:
static void cvFindFeatures(
	IntPtr tr, 
	IntPtr desc, 
	IntPtr results, 
	IntPtr dist, 
	int k, 
	int emax
)
F#
static member cvFindFeatures : 
        tr : IntPtr * 
        desc : IntPtr * 
        results : IntPtr * 
        dist : IntPtr * 
        k : int * 
        emax : int -> unit 

Parameters

tr
Type: System..::..IntPtr
Pointer to kd-tree index of reference vectors
desc
Type: System..::..IntPtr
m x d matrix of (row-)vectors to find the nearest neighbors of
results
Type: System..::..IntPtr
m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found
dist
Type: System..::..IntPtr
m x k matrix of distances to k nearest neighbors
k
Type: System..::..Int32
The number of neighbors to find
emax
Type: System..::..Int32
For k-d tree only: the maximum number of leaves to visit.

Remarks

In case of k-d tree: Finds (with high probability) the k nearest neighbors in tr for each of the given (row-)vectors in desc, using best-bin-first searching ([Beis97]). The complexity of the entire operation is at most O(m*emax*log2(n)), where n is the number of vectors in the tree

See Also