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ORBmatcher.cc
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/**
* This file is part of ORB-SLAM3
*
* Copyright (C) 2017-2021 Carlos Campos, Richard Elvira, Juan J. Gómez Rodríguez, José M.M. Montiel and Juan D. Tardós, University of Zaragoza.
* Copyright (C) 2014-2016 Raúl Mur-Artal, José M.M. Montiel and Juan D. Tardós, University of Zaragoza.
*
* ORB-SLAM3 is free software: you can redistribute it and/or modify it under the terms of the GNU General Public
* License as published by the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* ORB-SLAM3 is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even
* the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along with ORB-SLAM3.
* If not, see <http://www.gnu.org/licenses/>.
*/
#include "ORBmatcher.h"
#include<limits.h>
#include<opencv2/core/core.hpp>
#include "Thirdparty/DBoW2/DBoW2/FeatureVector.h"
#include<stdint-gcc.h>
using namespace std;
namespace ORB_SLAM3
{
const int ORBmatcher::TH_HIGH = 100;
const int ORBmatcher::TH_LOW = 50;
const int ORBmatcher::HISTO_LENGTH = 30;
ORBmatcher::ORBmatcher(float nnratio, bool checkOri): mfNNratio(nnratio), mbCheckOrientation(checkOri)
{
}
int ORBmatcher::SearchByProjection(Frame &F, const vector<MapPoint*> &vpMapPoints, const float th, const bool bFarPoints, const float thFarPoints)
{
int nmatches=0, left = 0, right = 0;
const bool bFactor = th!=1.0;
for(size_t iMP=0; iMP<vpMapPoints.size(); iMP++)
{
MapPoint* pMP = vpMapPoints[iMP];
if(!pMP->mbTrackInView && !pMP->mbTrackInViewR)
continue;
if(bFarPoints && pMP->mTrackDepth>thFarPoints)
continue;
if(pMP->isBad())
continue;
if(pMP->mbTrackInView)
{
const int &nPredictedLevel = pMP->mnTrackScaleLevel;
// The size of the window will depend on the viewing direction
float r = RadiusByViewingCos(pMP->mTrackViewCos);
if(bFactor)
r*=th;
const vector<size_t> vIndices =
F.GetFeaturesInArea(pMP->mTrackProjX,pMP->mTrackProjY,r*F.mvScaleFactors[nPredictedLevel],nPredictedLevel-1,nPredictedLevel);
if(!vIndices.empty()){
const cv::Mat MPdescriptor = pMP->GetDescriptor();
int bestDist=256;
int bestLevel= -1;
int bestDist2=256;
int bestLevel2 = -1;
int bestIdx =-1 ;
// Get best and second matches with near keypoints
for(vector<size_t>::const_iterator vit=vIndices.begin(), vend=vIndices.end(); vit!=vend; vit++)
{
const size_t idx = *vit;
if(F.mvpMapPoints[idx])
if(F.mvpMapPoints[idx]->Observations()>0)
continue;
if(F.Nleft == -1 && F.mvuRight[idx]>0)
{
const float er = fabs(pMP->mTrackProjXR-F.mvuRight[idx]);
if(er>r*F.mvScaleFactors[nPredictedLevel])
continue;
}
const cv::Mat &d = F.mDescriptors.row(idx);
const int dist = DescriptorDistance(MPdescriptor,d);
if(dist<bestDist)
{
bestDist2=bestDist;
bestDist=dist;
bestLevel2 = bestLevel;
bestLevel = (F.Nleft == -1) ? F.mvKeysUn[idx].octave
: (idx < F.Nleft) ? F.mvKeys[idx].octave
: F.mvKeysRight[idx - F.Nleft].octave;
bestIdx=idx;
}
else if(dist<bestDist2)
{
bestLevel2 = (F.Nleft == -1) ? F.mvKeysUn[idx].octave
: (idx < F.Nleft) ? F.mvKeys[idx].octave
: F.mvKeysRight[idx - F.Nleft].octave;
bestDist2=dist;
}
}
// Apply ratio to second match (only if best and second are in the same scale level)
if(bestDist<=TH_HIGH)
{
if(bestLevel==bestLevel2 && bestDist>mfNNratio*bestDist2)
continue;
if(bestLevel!=bestLevel2 || bestDist<=mfNNratio*bestDist2){
F.mvpMapPoints[bestIdx]=pMP;
if(F.Nleft != -1 && F.mvLeftToRightMatch[bestIdx] != -1){ //Also match with the stereo observation at right camera
F.mvpMapPoints[F.mvLeftToRightMatch[bestIdx] + F.Nleft] = pMP;
nmatches++;
right++;
}
nmatches++;
left++;
}
}
}
}
if(F.Nleft != -1 && pMP->mbTrackInViewR){
const int &nPredictedLevel = pMP->mnTrackScaleLevelR;
if(nPredictedLevel != -1){
float r = RadiusByViewingCos(pMP->mTrackViewCosR);
const vector<size_t> vIndices =
F.GetFeaturesInArea(pMP->mTrackProjXR,pMP->mTrackProjYR,r*F.mvScaleFactors[nPredictedLevel],nPredictedLevel-1,nPredictedLevel,true);
if(vIndices.empty())
continue;
const cv::Mat MPdescriptor = pMP->GetDescriptor();
int bestDist=256;
int bestLevel= -1;
int bestDist2=256;
int bestLevel2 = -1;
int bestIdx =-1 ;
// Get best and second matches with near keypoints
for(vector<size_t>::const_iterator vit=vIndices.begin(), vend=vIndices.end(); vit!=vend; vit++)
{
const size_t idx = *vit;
if(F.mvpMapPoints[idx + F.Nleft])
if(F.mvpMapPoints[idx + F.Nleft]->Observations()>0)
continue;
const cv::Mat &d = F.mDescriptors.row(idx + F.Nleft);
const int dist = DescriptorDistance(MPdescriptor,d);
if(dist<bestDist)
{
bestDist2=bestDist;
bestDist=dist;
bestLevel2 = bestLevel;
bestLevel = F.mvKeysRight[idx].octave;
bestIdx=idx;
}
else if(dist<bestDist2)
{
bestLevel2 = F.mvKeysRight[idx].octave;
bestDist2=dist;
}
}
// Apply ratio to second match (only if best and second are in the same scale level)
if(bestDist<=TH_HIGH)
{
if(bestLevel==bestLevel2 && bestDist>mfNNratio*bestDist2)
continue;
if(F.Nleft != -1 && F.mvRightToLeftMatch[bestIdx] != -1){ //Also match with the stereo observation at right camera
F.mvpMapPoints[F.mvRightToLeftMatch[bestIdx]] = pMP;
nmatches++;
left++;
}
F.mvpMapPoints[bestIdx + F.Nleft]=pMP;
nmatches++;
right++;
}
}
}
}
return nmatches;
}
float ORBmatcher::RadiusByViewingCos(const float &viewCos)
{
if(viewCos>0.998)
return 2.5;
else
return 4.0;
}
int ORBmatcher::SearchByBoW(KeyFrame* pKF,Frame &F, vector<MapPoint*> &vpMapPointMatches)
{
const vector<MapPoint*> vpMapPointsKF = pKF->GetMapPointMatches();
vpMapPointMatches = vector<MapPoint*>(F.N,static_cast<MapPoint*>(NULL));
const DBoW2::FeatureVector &vFeatVecKF = pKF->mFeatVec;
int nmatches=0;
vector<int> rotHist[HISTO_LENGTH];
for(int i=0;i<HISTO_LENGTH;i++)
rotHist[i].reserve(500);
const float factor = 1.0f/HISTO_LENGTH;
// We perform the matching over ORB that belong to the same vocabulary node (at a certain level)
DBoW2::FeatureVector::const_iterator KFit = vFeatVecKF.begin();
DBoW2::FeatureVector::const_iterator Fit = F.mFeatVec.begin();
DBoW2::FeatureVector::const_iterator KFend = vFeatVecKF.end();
DBoW2::FeatureVector::const_iterator Fend = F.mFeatVec.end();
while(KFit != KFend && Fit != Fend)
{
if(KFit->first == Fit->first)
{
const vector<unsigned int> vIndicesKF = KFit->second;
const vector<unsigned int> vIndicesF = Fit->second;
for(size_t iKF=0; iKF<vIndicesKF.size(); iKF++)
{
const unsigned int realIdxKF = vIndicesKF[iKF];
MapPoint* pMP = vpMapPointsKF[realIdxKF];
if(!pMP)
continue;
if(pMP->isBad())
continue;
const cv::Mat &dKF= pKF->mDescriptors.row(realIdxKF);
int bestDist1=256;
int bestIdxF =-1 ;
int bestDist2=256;
int bestDist1R=256;
int bestIdxFR =-1 ;
int bestDist2R=256;
for(size_t iF=0; iF<vIndicesF.size(); iF++)
{
if(F.Nleft == -1){
const unsigned int realIdxF = vIndicesF[iF];
if(vpMapPointMatches[realIdxF])
continue;
const cv::Mat &dF = F.mDescriptors.row(realIdxF);
const int dist = DescriptorDistance(dKF,dF);
if(dist<bestDist1)
{
bestDist2=bestDist1;
bestDist1=dist;
bestIdxF=realIdxF;
}
else if(dist<bestDist2)
{
bestDist2=dist;
}
}
else{
const unsigned int realIdxF = vIndicesF[iF];
if(vpMapPointMatches[realIdxF])
continue;
const cv::Mat &dF = F.mDescriptors.row(realIdxF);
const int dist = DescriptorDistance(dKF,dF);
if(realIdxF < F.Nleft && dist<bestDist1){
bestDist2=bestDist1;
bestDist1=dist;
bestIdxF=realIdxF;
}
else if(realIdxF < F.Nleft && dist<bestDist2){
bestDist2=dist;
}
if(realIdxF >= F.Nleft && dist<bestDist1R){
bestDist2R=bestDist1R;
bestDist1R=dist;
bestIdxFR=realIdxF;
}
else if(realIdxF >= F.Nleft && dist<bestDist2R){
bestDist2R=dist;
}
}
}
if(bestDist1<=TH_LOW)
{
if(static_cast<float>(bestDist1)<mfNNratio*static_cast<float>(bestDist2))
{
vpMapPointMatches[bestIdxF]=pMP;
const cv::KeyPoint &kp =
(!pKF->mpCamera2) ? pKF->mvKeysUn[realIdxKF] :
(realIdxKF >= pKF -> NLeft) ? pKF -> mvKeysRight[realIdxKF - pKF -> NLeft]
: pKF -> mvKeys[realIdxKF];
if(mbCheckOrientation)
{
cv::KeyPoint &Fkp =
(!pKF->mpCamera2 || F.Nleft == -1) ? F.mvKeys[bestIdxF] :
(bestIdxF >= F.Nleft) ? F.mvKeysRight[bestIdxF - F.Nleft]
: F.mvKeys[bestIdxF];
float rot = kp.angle-Fkp.angle;
if(rot<0.0)
rot+=360.0f;
int bin = round(rot*factor);
if(bin==HISTO_LENGTH)
bin=0;
assert(bin>=0 && bin<HISTO_LENGTH);
rotHist[bin].push_back(bestIdxF);
}
nmatches++;
}
if(bestDist1R<=TH_LOW)
{
if(static_cast<float>(bestDist1R)<mfNNratio*static_cast<float>(bestDist2R) || true)
{
vpMapPointMatches[bestIdxFR]=pMP;
const cv::KeyPoint &kp =
(!pKF->mpCamera2) ? pKF->mvKeysUn[realIdxKF] :
(realIdxKF >= pKF -> NLeft) ? pKF -> mvKeysRight[realIdxKF - pKF -> NLeft]
: pKF -> mvKeys[realIdxKF];
if(mbCheckOrientation)
{
cv::KeyPoint &Fkp =
(!F.mpCamera2) ? F.mvKeys[bestIdxFR] :
(bestIdxFR >= F.Nleft) ? F.mvKeysRight[bestIdxFR - F.Nleft]
: F.mvKeys[bestIdxFR];
float rot = kp.angle-Fkp.angle;
if(rot<0.0)
rot+=360.0f;
int bin = round(rot*factor);
if(bin==HISTO_LENGTH)
bin=0;
assert(bin>=0 && bin<HISTO_LENGTH);
rotHist[bin].push_back(bestIdxFR);
}
nmatches++;
}
}
}
}
KFit++;
Fit++;
}
else if(KFit->first < Fit->first)
{
KFit = vFeatVecKF.lower_bound(Fit->first);
}
else
{
Fit = F.mFeatVec.lower_bound(KFit->first);
}
}
if(mbCheckOrientation)
{
int ind1=-1;
int ind2=-1;
int ind3=-1;
ComputeThreeMaxima(rotHist,HISTO_LENGTH,ind1,ind2,ind3);
for(int i=0; i<HISTO_LENGTH; i++)
{
if(i==ind1 || i==ind2 || i==ind3)
continue;
for(size_t j=0, jend=rotHist[i].size(); j<jend; j++)
{
vpMapPointMatches[rotHist[i][j]]=static_cast<MapPoint*>(NULL);
nmatches--;
}
}
}
return nmatches;
}
int ORBmatcher::SearchByProjection(KeyFrame* pKF, Sophus::Sim3f &Scw, const vector<MapPoint*> &vpPoints,
vector<MapPoint*> &vpMatched, int th, float ratioHamming)
{
// Get Calibration Parameters for later projection
const float &fx = pKF->fx;
const float &fy = pKF->fy;
const float &cx = pKF->cx;
const float &cy = pKF->cy;
Sophus::SE3f Tcw = Sophus::SE3f(Scw.rotationMatrix(),Scw.translation()/Scw.scale());
Eigen::Vector3f Ow = Tcw.inverse().translation();
// Set of MapPoints already found in the KeyFrame
set<MapPoint*> spAlreadyFound(vpMatched.begin(), vpMatched.end());
spAlreadyFound.erase(static_cast<MapPoint*>(NULL));
int nmatches=0;
// For each Candidate MapPoint Project and Match
for(int iMP=0, iendMP=vpPoints.size(); iMP<iendMP; iMP++)
{
MapPoint* pMP = vpPoints[iMP];
// Discard Bad MapPoints and already found
if(pMP->isBad() || spAlreadyFound.count(pMP))
continue;
// Get 3D Coords.
Eigen::Vector3f p3Dw = pMP->GetWorldPos();
// Transform into Camera Coords.
Eigen::Vector3f p3Dc = Tcw * p3Dw;
// Depth must be positive
if(p3Dc(2)<0.0)
continue;
// Project into Image
const Eigen::Vector2f uv = pKF->mpCamera->project(p3Dc);
// Point must be inside the image
if(!pKF->IsInImage(uv(0),uv(1)))
continue;
// Depth must be inside the scale invariance region of the point
const float maxDistance = pMP->GetMaxDistanceInvariance();
const float minDistance = pMP->GetMinDistanceInvariance();
Eigen::Vector3f PO = p3Dw-Ow;
const float dist = PO.norm();
if(dist<minDistance || dist>maxDistance)
continue;
// Viewing angle must be less than 60 deg
Eigen::Vector3f Pn = pMP->GetNormal();
if(PO.dot(Pn)<0.5*dist)
continue;
int nPredictedLevel = pMP->PredictScale(dist,pKF);
// Search in a radius
const float radius = th*pKF->mvScaleFactors[nPredictedLevel];
const vector<size_t> vIndices = pKF->GetFeaturesInArea(uv(0),uv(1),radius);
if(vIndices.empty())
continue;
// Match to the most similar keypoint in the radius
const cv::Mat dMP = pMP->GetDescriptor();
int bestDist = 256;
int bestIdx = -1;
for(vector<size_t>::const_iterator vit=vIndices.begin(), vend=vIndices.end(); vit!=vend; vit++)
{
const size_t idx = *vit;
if(vpMatched[idx])
continue;
const int &kpLevel= pKF->mvKeysUn[idx].octave;
if(kpLevel<nPredictedLevel-1 || kpLevel>nPredictedLevel)
continue;
const cv::Mat &dKF = pKF->mDescriptors.row(idx);
const int dist = DescriptorDistance(dMP,dKF);
if(dist<bestDist)
{
bestDist = dist;
bestIdx = idx;
}
}
if(bestDist<=TH_LOW*ratioHamming)
{
vpMatched[bestIdx]=pMP;
nmatches++;
}
}
return nmatches;
}
int ORBmatcher::SearchByProjection(KeyFrame* pKF, Sophus::Sim3<float> &Scw, const std::vector<MapPoint*> &vpPoints, const std::vector<KeyFrame*> &vpPointsKFs,
std::vector<MapPoint*> &vpMatched, std::vector<KeyFrame*> &vpMatchedKF, int th, float ratioHamming)
{
// Get Calibration Parameters for later projection
const float &fx = pKF->fx;
const float &fy = pKF->fy;
const float &cx = pKF->cx;
const float &cy = pKF->cy;
Sophus::SE3f Tcw = Sophus::SE3f(Scw.rotationMatrix(),Scw.translation()/Scw.scale());
Eigen::Vector3f Ow = Tcw.inverse().translation();
// Set of MapPoints already found in the KeyFrame
set<MapPoint*> spAlreadyFound(vpMatched.begin(), vpMatched.end());
spAlreadyFound.erase(static_cast<MapPoint*>(NULL));
int nmatches=0;
// For each Candidate MapPoint Project and Match
for(int iMP=0, iendMP=vpPoints.size(); iMP<iendMP; iMP++)
{
MapPoint* pMP = vpPoints[iMP];
KeyFrame* pKFi = vpPointsKFs[iMP];
// Discard Bad MapPoints and already found
if(pMP->isBad() || spAlreadyFound.count(pMP))
continue;
// Get 3D Coords.
Eigen::Vector3f p3Dw = pMP->GetWorldPos();
// Transform into Camera Coords.
Eigen::Vector3f p3Dc = Tcw * p3Dw;
// Depth must be positive
if(p3Dc(2)<0.0)
continue;
// Project into Image
const float invz = 1/p3Dc(2);
const float x = p3Dc(0)*invz;
const float y = p3Dc(1)*invz;
const float u = fx*x+cx;
const float v = fy*y+cy;
// Point must be inside the image
if(!pKF->IsInImage(u,v))
continue;
// Depth must be inside the scale invariance region of the point
const float maxDistance = pMP->GetMaxDistanceInvariance();
const float minDistance = pMP->GetMinDistanceInvariance();
Eigen::Vector3f PO = p3Dw-Ow;
const float dist = PO.norm();
if(dist<minDistance || dist>maxDistance)
continue;
// Viewing angle must be less than 60 deg
Eigen::Vector3f Pn = pMP->GetNormal();
if(PO.dot(Pn)<0.5*dist)
continue;
int nPredictedLevel = pMP->PredictScale(dist,pKF);
// Search in a radius
const float radius = th*pKF->mvScaleFactors[nPredictedLevel];
const vector<size_t> vIndices = pKF->GetFeaturesInArea(u,v,radius);
if(vIndices.empty())
continue;
// Match to the most similar keypoint in the radius
const cv::Mat dMP = pMP->GetDescriptor();
int bestDist = 256;
int bestIdx = -1;
for(vector<size_t>::const_iterator vit=vIndices.begin(), vend=vIndices.end(); vit!=vend; vit++)
{
const size_t idx = *vit;
if(vpMatched[idx])
continue;
const int &kpLevel= pKF->mvKeysUn[idx].octave;
if(kpLevel<nPredictedLevel-1 || kpLevel>nPredictedLevel)
continue;
const cv::Mat &dKF = pKF->mDescriptors.row(idx);
const int dist = DescriptorDistance(dMP,dKF);
if(dist<bestDist)
{
bestDist = dist;
bestIdx = idx;
}
}
if(bestDist<=TH_LOW*ratioHamming)
{
vpMatched[bestIdx] = pMP;
vpMatchedKF[bestIdx] = pKFi;
nmatches++;
}
}
return nmatches;
}
int ORBmatcher::SearchForInitialization(Frame &F1, Frame &F2, vector<cv::Point2f> &vbPrevMatched, vector<int> &vnMatches12, int windowSize)
{
int nmatches=0;
vnMatches12 = vector<int>(F1.mvKeysUn.size(),-1);
vector<int> rotHist[HISTO_LENGTH];
for(int i=0;i<HISTO_LENGTH;i++)
rotHist[i].reserve(500);
const float factor = 1.0f/HISTO_LENGTH;
vector<int> vMatchedDistance(F2.mvKeysUn.size(),INT_MAX);
vector<int> vnMatches21(F2.mvKeysUn.size(),-1);
for(size_t i1=0, iend1=F1.mvKeysUn.size(); i1<iend1; i1++)
{
cv::KeyPoint kp1 = F1.mvKeysUn[i1];
int level1 = kp1.octave;
if(level1>0)
continue;
vector<size_t> vIndices2 = F2.GetFeaturesInArea(vbPrevMatched[i1].x,vbPrevMatched[i1].y, windowSize,level1,level1);
if(vIndices2.empty())
continue;
cv::Mat d1 = F1.mDescriptors.row(i1);
int bestDist = INT_MAX;
int bestDist2 = INT_MAX;
int bestIdx2 = -1;
for(vector<size_t>::iterator vit=vIndices2.begin(); vit!=vIndices2.end(); vit++)
{
size_t i2 = *vit;
cv::Mat d2 = F2.mDescriptors.row(i2);
int dist = DescriptorDistance(d1,d2);
if(vMatchedDistance[i2]<=dist)
continue;
if(dist<bestDist)
{
bestDist2=bestDist;
bestDist=dist;
bestIdx2=i2;
}
else if(dist<bestDist2)
{
bestDist2=dist;
}
}
if(bestDist<=TH_LOW)
{
if(bestDist<(float)bestDist2*mfNNratio)
{
if(vnMatches21[bestIdx2]>=0)
{
vnMatches12[vnMatches21[bestIdx2]]=-1;
nmatches--;
}
vnMatches12[i1]=bestIdx2;
vnMatches21[bestIdx2]=i1;
vMatchedDistance[bestIdx2]=bestDist;
nmatches++;
if(mbCheckOrientation)
{
float rot = F1.mvKeysUn[i1].angle-F2.mvKeysUn[bestIdx2].angle;
if(rot<0.0)
rot+=360.0f;
int bin = round(rot*factor);
if(bin==HISTO_LENGTH)
bin=0;
assert(bin>=0 && bin<HISTO_LENGTH);
rotHist[bin].push_back(i1);
}
}
}
}
if(mbCheckOrientation)
{
int ind1=-1;
int ind2=-1;
int ind3=-1;
ComputeThreeMaxima(rotHist,HISTO_LENGTH,ind1,ind2,ind3);
for(int i=0; i<HISTO_LENGTH; i++)
{
if(i==ind1 || i==ind2 || i==ind3)
continue;
for(size_t j=0, jend=rotHist[i].size(); j<jend; j++)
{
int idx1 = rotHist[i][j];
if(vnMatches12[idx1]>=0)
{
vnMatches12[idx1]=-1;
nmatches--;
}
}
}
}
//Update prev matched
for(size_t i1=0, iend1=vnMatches12.size(); i1<iend1; i1++)
if(vnMatches12[i1]>=0)
vbPrevMatched[i1]=F2.mvKeysUn[vnMatches12[i1]].pt;
return nmatches;
}
int ORBmatcher::SearchByBoW(KeyFrame *pKF1, KeyFrame *pKF2, vector<MapPoint *> &vpMatches12)
{
const vector<cv::KeyPoint> &vKeysUn1 = pKF1->mvKeysUn;
const DBoW2::FeatureVector &vFeatVec1 = pKF1->mFeatVec;
const vector<MapPoint*> vpMapPoints1 = pKF1->GetMapPointMatches();
const cv::Mat &Descriptors1 = pKF1->mDescriptors;
const vector<cv::KeyPoint> &vKeysUn2 = pKF2->mvKeysUn;
const DBoW2::FeatureVector &vFeatVec2 = pKF2->mFeatVec;
const vector<MapPoint*> vpMapPoints2 = pKF2->GetMapPointMatches();
const cv::Mat &Descriptors2 = pKF2->mDescriptors;
vpMatches12 = vector<MapPoint*>(vpMapPoints1.size(),static_cast<MapPoint*>(NULL));
vector<bool> vbMatched2(vpMapPoints2.size(),false);
vector<int> rotHist[HISTO_LENGTH];
for(int i=0;i<HISTO_LENGTH;i++)
rotHist[i].reserve(500);
const float factor = 1.0f/HISTO_LENGTH;
int nmatches = 0;
DBoW2::FeatureVector::const_iterator f1it = vFeatVec1.begin();
DBoW2::FeatureVector::const_iterator f2it = vFeatVec2.begin();
DBoW2::FeatureVector::const_iterator f1end = vFeatVec1.end();
DBoW2::FeatureVector::const_iterator f2end = vFeatVec2.end();
while(f1it != f1end && f2it != f2end)
{
if(f1it->first == f2it->first)
{
for(size_t i1=0, iend1=f1it->second.size(); i1<iend1; i1++)
{
const size_t idx1 = f1it->second[i1];
if(pKF1 -> NLeft != -1 && idx1 >= pKF1 -> mvKeysUn.size()){
continue;
}
MapPoint* pMP1 = vpMapPoints1[idx1];
if(!pMP1)
continue;
if(pMP1->isBad())
continue;
const cv::Mat &d1 = Descriptors1.row(idx1);
int bestDist1=256;
int bestIdx2 =-1 ;
int bestDist2=256;
for(size_t i2=0, iend2=f2it->second.size(); i2<iend2; i2++)
{
const size_t idx2 = f2it->second[i2];
if(pKF2 -> NLeft != -1 && idx2 >= pKF2 -> mvKeysUn.size()){
continue;
}
MapPoint* pMP2 = vpMapPoints2[idx2];
if(vbMatched2[idx2] || !pMP2)
continue;
if(pMP2->isBad())
continue;
const cv::Mat &d2 = Descriptors2.row(idx2);
int dist = DescriptorDistance(d1,d2);
if(dist<bestDist1)
{
bestDist2=bestDist1;
bestDist1=dist;
bestIdx2=idx2;
}
else if(dist<bestDist2)
{
bestDist2=dist;
}
}
if(bestDist1<TH_LOW)
{
if(static_cast<float>(bestDist1)<mfNNratio*static_cast<float>(bestDist2))
{
vpMatches12[idx1]=vpMapPoints2[bestIdx2];
vbMatched2[bestIdx2]=true;
if(mbCheckOrientation)
{
float rot = vKeysUn1[idx1].angle-vKeysUn2[bestIdx2].angle;
if(rot<0.0)
rot+=360.0f;
int bin = round(rot*factor);
if(bin==HISTO_LENGTH)
bin=0;
assert(bin>=0 && bin<HISTO_LENGTH);
rotHist[bin].push_back(idx1);
}
nmatches++;
}
}
}
f1it++;
f2it++;
}
else if(f1it->first < f2it->first)
{
f1it = vFeatVec1.lower_bound(f2it->first);
}
else
{
f2it = vFeatVec2.lower_bound(f1it->first);
}
}
if(mbCheckOrientation)
{
int ind1=-1;
int ind2=-1;
int ind3=-1;
ComputeThreeMaxima(rotHist,HISTO_LENGTH,ind1,ind2,ind3);
for(int i=0; i<HISTO_LENGTH; i++)
{
if(i==ind1 || i==ind2 || i==ind3)
continue;
for(size_t j=0, jend=rotHist[i].size(); j<jend; j++)
{
vpMatches12[rotHist[i][j]]=static_cast<MapPoint*>(NULL);
nmatches--;
}
}
}
return nmatches;
}
int ORBmatcher::SearchForTriangulation(KeyFrame *pKF1, KeyFrame *pKF2,
vector<pair<size_t, size_t> > &vMatchedPairs, const bool bOnlyStereo, const bool bCoarse)
{
const DBoW2::FeatureVector &vFeatVec1 = pKF1->mFeatVec;
const DBoW2::FeatureVector &vFeatVec2 = pKF2->mFeatVec;
//Compute epipole in second image
Sophus::SE3f T1w = pKF1->GetPose();
Sophus::SE3f T2w = pKF2->GetPose();
Sophus::SE3f Tw2 = pKF2->GetPoseInverse(); // for convenience
Eigen::Vector3f Cw = pKF1->GetCameraCenter();
Eigen::Vector3f C2 = T2w * Cw;
Eigen::Vector2f ep = pKF2->mpCamera->project(C2);
Sophus::SE3f T12;
Sophus::SE3f Tll, Tlr, Trl, Trr;
Eigen::Matrix3f R12; // for fastest computation
Eigen::Vector3f t12; // for fastest computation
GeometricCamera* pCamera1 = pKF1->mpCamera, *pCamera2 = pKF2->mpCamera;
if(!pKF1->mpCamera2 && !pKF2->mpCamera2){
T12 = T1w * Tw2;
R12 = T12.rotationMatrix();
t12 = T12.translation();
}
else{
Sophus::SE3f Tr1w = pKF1->GetRightPose();
Sophus::SE3f Twr2 = pKF2->GetRightPoseInverse();
Tll = T1w * Tw2;
Tlr = T1w * Twr2;
Trl = Tr1w * Tw2;
Trr = Tr1w * Twr2;
}
Eigen::Matrix3f Rll = Tll.rotationMatrix(), Rlr = Tlr.rotationMatrix(), Rrl = Trl.rotationMatrix(), Rrr = Trr.rotationMatrix();
Eigen::Vector3f tll = Tll.translation(), tlr = Tlr.translation(), trl = Trl.translation(), trr = Trr.translation();
// Find matches between not tracked keypoints
// Matching speed-up by ORB Vocabulary
// Compare only ORB that share the same node
int nmatches=0;
vector<bool> vbMatched2(pKF2->N,false);
vector<int> vMatches12(pKF1->N,-1);
vector<int> rotHist[HISTO_LENGTH];
for(int i=0;i<HISTO_LENGTH;i++)
rotHist[i].reserve(500);
const float factor = 1.0f/HISTO_LENGTH;
DBoW2::FeatureVector::const_iterator f1it = vFeatVec1.begin();
DBoW2::FeatureVector::const_iterator f2it = vFeatVec2.begin();
DBoW2::FeatureVector::const_iterator f1end = vFeatVec1.end();
DBoW2::FeatureVector::const_iterator f2end = vFeatVec2.end();
while(f1it!=f1end && f2it!=f2end)
{
if(f1it->first == f2it->first)
{
for(size_t i1=0, iend1=f1it->second.size(); i1<iend1; i1++)
{
const size_t idx1 = f1it->second[i1];
MapPoint* pMP1 = pKF1->GetMapPoint(idx1);
// If there is already a MapPoint skip
if(pMP1)
{
continue;
}
const bool bStereo1 = (!pKF1->mpCamera2 && pKF1->mvuRight[idx1]>=0);
if(bOnlyStereo)
if(!bStereo1)
continue;
const cv::KeyPoint &kp1 = (pKF1 -> NLeft == -1) ? pKF1->mvKeysUn[idx1]
: (idx1 < pKF1 -> NLeft) ? pKF1 -> mvKeys[idx1]
: pKF1 -> mvKeysRight[idx1 - pKF1 -> NLeft];
const bool bRight1 = (pKF1 -> NLeft == -1 || idx1 < pKF1 -> NLeft) ? false
: true;
const cv::Mat &d1 = pKF1->mDescriptors.row(idx1);
int bestDist = TH_LOW;
int bestIdx2 = -1;
for(size_t i2=0, iend2=f2it->second.size(); i2<iend2; i2++)
{
size_t idx2 = f2it->second[i2];