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/*
* Copyright (C) 2011 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*$Id: db_feature_matching.h,v 1.3 2011/06/17 14:03:30 mbansal Exp $*/
#ifndef DB_FEATURE_MATCHING_H
#define DB_FEATURE_MATCHING_H
/*****************************************************************
* Lean and mean begins here *
*****************************************************************/
/*!
* \defgroup FeatureMatching Feature Matching
*/
#include "db_utilities.h"
#include "db_utilities_constants.h"
DB_API void db_SignedSquareNormCorr21x21_PreAlign_u(short *patch,const unsigned char * const *f_img,int x_f,int y_f,float *sum,float *recip);
DB_API void db_SignedSquareNormCorr11x11_PreAlign_u(short *patch,const unsigned char * const *f_img,int x_f,int y_f,float *sum,float *recip);
float db_SignedSquareNormCorr21x21Aligned_Post_s(const short *f_patch,const short *g_patch,float fsum_gsum,float f_recip_g_recip);
float db_SignedSquareNormCorr11x11Aligned_Post_s(const short *f_patch,const short *g_patch,float fsum_gsum,float f_recip_g_recip);
class db_PointInfo_f
{
public:
/*Coordinates of point*/
int x;
int y;
/*Id nr of point*/
int id;
/*Best match score*/
double s;
/*Best match candidate*/
db_PointInfo_f *pir;
/*Precomputed coefficients
of image patch*/
float sum;
float recip;
/*Pointer to patch layout*/
const float *patch;
};
class db_Bucket_f
{
public:
db_PointInfo_f *ptr;
int nr;
};
class db_PointInfo_u
{
public:
/*Coordinates of point*/
int x;
int y;
/*Id nr of point*/
int id;
/*Best match score*/
double s;
/*Best match candidate*/
db_PointInfo_u *pir;
/*Precomputed coefficients
of image patch*/
float sum;
float recip;
/*Pointer to patch layout*/
const short *patch;
};
class db_Bucket_u
{
public:
db_PointInfo_u *ptr;
int nr;
};
/*!
* \class db_Matcher_f
* \ingroup FeatureMatching
* \brief Feature matcher for float images.
*
* Normalized correlation feature matcher for <b>float</b> images.
* Correlation window size is constant and set to 11x11.
* See \ref FeatureDetection to detect Harris corners.
* Images are managed with functions in \ref LMImageBasicUtilities.
*/
class DB_API db_Matcher_f
{
public:
db_Matcher_f();
~db_Matcher_f();
/*!
* Set parameters and pre-allocate memory. Return an upper bound
* on the number of matches.
* \param im_width width
* \param im_height height
* \param max_disparity maximum distance (as fraction of image size) between matches
* \param target_nr_corners maximum number of matches
* \return maximum number of matches
*/
unsigned long Init(int im_width,int im_height,
double max_disparity=DB_DEFAULT_MAX_DISPARITY,
int target_nr_corners=DB_DEFAULT_TARGET_NR_CORNERS);
/*!
* Match two sets of features.
* If the prewarp H is not NULL it will be applied to the features
* in the right image before matching.
* Parameters id_l and id_r must point to arrays of size target_nr_corners
* (returned by Init()).
* The results of matching are in id_l and id_r.
* Interpretaqtion of results: if id_l[i] = m and id_r[i] = n,
* feature at (x_l[m],y_l[m]) matched to (x_r[n],y_r[n]).
* \param l_img left image
* \param r_img right image
* \param x_l left x coordinates of features
* \param y_l left y coordinates of features
* \param nr_l number of features in left image
* \param x_r right x coordinates of features
* \param y_r right y coordinates of features
* \param nr_r number of features in right image
* \param id_l indices of left features that matched
* \param id_r indices of right features that matched
* \param nr_matches number of features actually matched
* \param H image homography (prewarp) to be applied to right image features
*/
void Match(const float * const *l_img,const float * const *r_img,
const double *x_l,const double *y_l,int nr_l,const double *x_r,const double *y_r,int nr_r,
int *id_l,int *id_r,int *nr_matches,const double H[9]=0);
protected:
void Clean();
int m_w,m_h,m_bw,m_bh,m_nr_h,m_nr_v,m_bd,m_target;
unsigned long m_kA,m_kB;
db_Bucket_f **m_bp_l;
db_Bucket_f **m_bp_r;
float *m_patch_space,*m_aligned_patch_space;
};
/*!
* \class db_Matcher_u
* \ingroup FeatureMatching
* \brief Feature matcher for byte images.
*
* Normalized correlation feature matcher for <b>byte</b> images.
* Correlation window size is constant and set to 11x11.
* See \ref FeatureDetection to detect Harris corners.
* Images are managed with functions in \ref LMImageBasicUtilities.
*
* If the prewarp matrix H is supplied, the feature coordinates are warped by H before being placed in
* appropriate buckets. If H is an affine transform and the "affine" parameter is set to 1 or 2,
* then the correlation patches themselves are warped before being placed in the patch space.
*/
class DB_API db_Matcher_u
{
public:
db_Matcher_u();
int GetPatchSize(){return 11;};
virtual ~db_Matcher_u();
/*!
Copy ctor duplicates settings.
Memory not copied.
*/
db_Matcher_u(const db_Matcher_u& cm);
/*!
Assignment optor duplicates settings
Memory not copied.
*/
db_Matcher_u& operator= (const db_Matcher_u& cm);
/*!
* Set parameters and pre-allocate memory. Return an upper bound
* on the number of matches.
* If max_disparity_v is DB_DEFAULT_NO_DISPARITY, look for matches
* in a ellipse around a feature of radius max_disparity*im_width by max_disparity*im_height.
* If max_disparity_v is specified, use a rectangle max_disparity*im_width by max_disparity_v*im_height.
* \param im_width width
* \param im_height height
* \param max_disparity maximum distance (as fraction of image size) between matches
* \param target_nr_corners maximum number of matches
* \param max_disparity_v maximum vertical disparity (distance between matches)
* \param use_smaller_matching_window if set to true, uses a correlation window of 5x5 instead of the default 11x11
* \return maximum number of matches
*/
virtual unsigned long Init(int im_width,int im_height,
double max_disparity=DB_DEFAULT_MAX_DISPARITY,
int target_nr_corners=DB_DEFAULT_TARGET_NR_CORNERS,
double max_disparity_v=DB_DEFAULT_NO_DISPARITY,
bool use_smaller_matching_window=false, int use_21=0);
/*!
* Match two sets of features.
* If the prewarp H is not NULL it will be applied to the features
* in the right image before matching.
* Parameters id_l and id_r must point to arrays of size target_nr_corners
* (returned by Init()).
* The results of matching are in id_l and id_r.
* Interpretaqtion of results: if id_l[i] = m and id_r[i] = n,
* feature at (x_l[m],y_l[m]) matched to (x_r[n],y_r[n]).
* \param l_img left image
* \param r_img right image
* \param x_l left x coordinates of features
* \param y_l left y coordinates of features
* \param nr_l number of features in left image
* \param x_r right x coordinates of features
* \param y_r right y coordinates of features
* \param nr_r number of features in right image
* \param id_l indices of left features that matched
* \param id_r indices of right features that matched
* \param nr_matches number of features actually matched
* \param H image homography (prewarp) to be applied to right image features
* \param affine prewarp the 11x11 patches by given affine transform. 0 means no warping,
1 means nearest neighbor, 2 means bilinear warping.
*/
virtual void Match(const unsigned char * const *l_img,const unsigned char * const *r_img,
const double *x_l,const double *y_l,int nr_l,const double *x_r,const double *y_r,int nr_r,
int *id_l,int *id_r,int *nr_matches,const double H[9]=0,int affine=0);
/*!
* Checks if Init() was called.
* \return 1 if Init() was called, 0 otherwise.
*/
int IsAllocated();
protected:
virtual void Clean();
int m_w,m_h,m_bw,m_bh,m_nr_h,m_nr_v,m_bd,m_target;
unsigned long m_kA,m_kB;
db_Bucket_u **m_bp_l;
db_Bucket_u **m_bp_r;
short *m_patch_space,*m_aligned_patch_space;
double m_max_disparity, m_max_disparity_v;
int m_rect_window;
bool m_use_smaller_matching_window;
int m_use_21;
};
#endif /*DB_FEATURE_MATCHING_H*/