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

Namespace: Emgu.CV
Assembly: Emgu.CV (in Emgu.CV.dll) Version: 2.2.1.1150 (2.2.1.1150)

Syntax

         
 C#  Visual Basic  Visual C++ 
public void FindFeatures(
	float[][] descriptors,
	out Matrix<int> results,
	out Matrix<double> dist,
	int k,
	int emax
)
Public Sub FindFeatures ( _
	descriptors As Single()(), _
	<OutAttribute> ByRef results As Matrix(Of Integer), _
	<OutAttribute> ByRef dist As Matrix(Of Double), _
	k As Integer, _
	emax As Integer _
)
public:
void FindFeatures(
	array<array<float>^>^ descriptors, 
	[OutAttribute] Matrix<int>^% results, 
	[OutAttribute] Matrix<double>^% dist, 
	int k, 
	int emax
)

Parameters

descriptors
array<array<Single>[]()[][]>[]()[][]
The m feature descriptors to be searched from the feature tree
results
Matrix<(Of <(<'Int32>)>)>%
The results of the best k matched from the feature tree. A m x k matrix. Contains -1 in some columns if fewer than k neighbors found. For each row the k neareast neighbors are not sorted. To findout the closet neighbour, look at the output matrix dist.
dist
Matrix<(Of <(<'Double>)>)>%
A m x k Matrix of the distances to k nearest neighbors
k
Int32
The number of neighbors to find
emax
Int32
For k-d tree only: the maximum number of leaves to visit. Use 20 if not sure

See Also