PARP Research Group University of Murcia, Spain


examples/OpenCV/siftDetector/hess/kdtree.h File Reference

#include "cxcore.h"

Go to the source code of this file.

Classes

struct  kd_node

Functions

struct kd_nodekdtree_build (struct feature *features, int n)
int kdtree_bbf_knn (struct kd_node *kd_root, struct feature *feat, int k, struct feature ***nbrs, int max_nn_chks)
int kdtree_bbf_spatial_knn (struct kd_node *kd_root, struct feature *feat, int k, struct feature ***nbrs, int max_nn_chks, CvRect rect, int model)
void kdtree_release (struct kd_node *kd_root)


Detailed Description

Functions and structures for maintaining a k-d tree database of image features.

For more information, refer to:

Beis, J. S. and Lowe, D. G. Shape indexing using approximate nearest-neighbor search in high-dimensional spaces. In Conference on Computer Vision and Pattern Recognition (CVPR) (2003), pp. 1000--1006.

Copyright (C) 2006-2007 Rob Hess <hess@eecs.oregonstate.edu>

Version:
1.1.1-20070913

Definition in file kdtree.h.


Function Documentation

int kdtree_bbf_knn ( struct kd_node kd_root,
struct feature feat,
int  k,
struct feature ***  nbrs,
int  max_nn_chks 
)

Finds an image feature's approximate k nearest neighbors in a kd tree using Best Bin First search.

Parameters:
kd_root root of an image feature kd tree
feat image feature for whose neighbors to search
k number of neighbors to find
nbrs pointer to an array in which to store pointers to neighbors in order of increasing descriptor distance
max_nn_chks search is cut off after examining this many tree entries
Returns:
Returns the number of neighbors found and stored in nbrs, or -1 on error.

Definition at line 93 of file kdtree.cpp.

int kdtree_bbf_spatial_knn ( struct kd_node kd_root,
struct feature feat,
int  k,
struct feature ***  nbrs,
int  max_nn_chks,
CvRect  rect,
int  model 
)

Finds an image feature's approximate k nearest neighbors within a specified spatial region in a kd tree using Best Bin First search.

Parameters:
kd_root root of an image feature kd tree
feat image feature for whose neighbors to search
k number of neighbors to find
nbrs pointer to an array in which to store pointers to neighbors in order of increasing descriptor distance
max_nn_chks search is cut off after examining this many tree entries
rect rectangular region in which to search for neighbors
model if true, spatial search is based on kdtree features' model locations; otherwise it is based on their image locations
Returns:
Returns the number of neighbors found and stored in nbrs (in case k neighbors could not be found before examining max_nn_checks keypoint entries).

Definition at line 191 of file kdtree.cpp.

struct kd_node* kdtree_build ( struct feature features,
int  n 
) [read]

A function to build a k-d tree database from keypoints in an array.

Parameters:
features an array of features
n the number of features in features
Returns:
Returns the root of a kd tree built from features.

Definition at line 60 of file kdtree.cpp.

void kdtree_release ( struct kd_node kd_root  ) 

De-allocates memory held by a kd tree

Parameters:
kd_root pointer to the root of a kd tree

Definition at line 228 of file kdtree.cpp.




QVision framework. PARP research group, copyright 2007, 2008.