ORBSLAM2源码学习(5) KeyFrame类
先上代码,再做总结
#ifndef KEYFRAME_H
#define KEYFRAME_H
#include "MapPoint.h"
#include "Thirdparty/DBoW2/DBoW2/BowVector.h"
#include "Thirdparty/DBoW2/DBoW2/FeatureVector.h"
#include "ORBVocabulary.h"
#include "ORBextractor.h"
#include "Frame.h"
#include "KeyFrameDatabase.h"
#include <mutex>
namespace ORB_SLAM2
{
class Map;
class MapPoint;
class Frame;
class KeyFrameDatabase;
/* KeyFrame
* 关键帧,和普通的Frame不一样,但是可以由Frame来构造
* 许多数据会被三个线程同时访问*/
class KeyFrame
{
public:
KeyFrame(Frame &F, Map* pMap, KeyFrameDatabase* pKFDB);
// Pose functions
void SetPose(const cv::Mat &Tcw);
cv::Mat GetPose();
cv::Mat GetPoseInverse();
cv::Mat GetCameraCenter();
cv::Mat GetStereoCenter();
cv::Mat GetRotation();
cv::Mat GetTranslation();
// Bag of Words Representation
void ComputeBoW();
// Covisibility graph functions
void AddConnection(KeyFrame* pKF, const int &weight);
void EraseConnection(KeyFrame* pKF);
void UpdateConnections();
void UpdateBestCovisibles();
std::set<KeyFrame *> GetConnectedKeyFrames();
std::vector<KeyFrame* > GetVectorCovisibleKeyFrames();
std::vector<KeyFrame*> GetBestCovisibilityKeyFrames(const int &N);
std::vector<KeyFrame*> GetCovisiblesByWeight(const int &w);
int GetWeight(KeyFrame* pKF);
// Spanning tree functions
void AddChild(KeyFrame* pKF);
void EraseChild(KeyFrame* pKF);
void ChangeParent(KeyFrame* pKF);
std::set<KeyFrame*> GetChilds();
KeyFrame* GetParent();
bool hasChild(KeyFrame* pKF);
// Loop Edges
void AddLoopEdge(KeyFrame* pKF);
std::set<KeyFrame*> GetLoopEdges();
// MapPoint observation functions
void AddMapPoint(MapPoint* pMP, const size_t &idx);
void EraseMapPointMatch(const size_t &idx);
void EraseMapPointMatch(MapPoint* pMP);
void ReplaceMapPointMatch(const size_t &idx, MapPoint* pMP);
std::set<MapPoint*> GetMapPoints();
std::vector<MapPoint*> GetMapPointMatches();
int TrackedMapPoints(const int &minObs);
MapPoint* GetMapPoint(const size_t &idx);
// KeyPoint functions
std::vector<size_t> GetFeaturesInArea(const float &x, const float &y, const float &r) const;
cv::Mat UnprojectStereo(int i);
// Image
bool IsInImage(const float &x, const float &y) const;
// Enable/Disable bad flag changes
void SetNotErase();
void SetErase();
// Set/check bad flag
void SetBadFlag();
bool isBad();
// Compute Scene Depth (q=2 median). Used in monocular.
float ComputeSceneMedianDepth(const int q);
static bool weightComp( int a, int b)
{
return a>b;
}
static bool lId(KeyFrame* pKF1, KeyFrame* pKF2)
{
return pKF1->mnId<pKF2->mnId;
}
// The following variables are accesed from only 1 thread or never change (no mutex needed).
public:
static long unsigned int nNextId;
long unsigned int mnId;
// 每个KeyFrame基本属性是它是一个Frame,KeyFrame初始化的时候需要Frame,
// mnFrameId记录了该KeyFrame是由哪个Frame初始化的
const long unsigned int mnFrameId;
const double mTimeStamp;
// Grid (to speed up feature matching)
const int mnGridCols;
const int mnGridRows;
const float mfGridElementWidthInv;
const float mfGridElementHeightInv;
// Variables used by the tracking
long unsigned int mnTrackReferenceForFrame;
long unsigned int mnFuseTargetForKF;
// Variables used by the local mapping
long unsigned int mnBALocalForKF;
long unsigned int mnBAFixedForKF;
// Variables used by the keyframe database
long unsigned int mnLoopQuery;
int mnLoopWords;
float mLoopScore;
long unsigned int mnRelocQuery;
int mnRelocWords;
float mRelocScore;
// Variables used by loop closing
cv::Mat mTcwGBA;
cv::Mat mTcwBefGBA;
long unsigned int mnBAGlobalForKF;
// Calibration parameters
const float fx, fy, cx, cy, invfx, invfy, mbf, mb, mThDepth;
// Number of KeyPoints
const int N;
// KeyPoints, stereo coordinate and descriptors (all associated by an index)
const std::vector<cv::KeyPoint> mvKeys;
const std::vector<cv::KeyPoint> mvKeysUn;
const std::vector<float> mvuRight; // negative value for monocular points
const std::vector<float> mvDepth; // negative value for monocular points
const cv::Mat mDescriptors;
//BoW
DBoW2::BowVector mBowVec; ///< Vector of words to represent images
DBoW2::FeatureVector mFeatVec; ///< Vector of nodes with indexes of local features
// Pose relative to parent (this is computed when bad flag is activated)
cv::Mat mTcp;
// Scale
const int mnScaleLevels;
const float mfScaleFactor;
const float mfLogScaleFactor;
const std::vector<float> mvScaleFactors;// 尺度,scale^n,scale=1.2,n为层数
const std::vector<float> mvLevelSigma2;
const std::vector<float> mvInvLevelSigma2;
// Image bounds and calibration
const int mnMinX;
const int mnMinY;
const int mnMaxX;
const int mnMaxY;
const cv::Mat mK;
// The following variables need to be accessed trough a mutex to be thread safe.
protected:
// SE3 Pose and camera center
cv::Mat Tcw;
cv::Mat Twc;
cv::Mat Ow;
cv::Mat Cw; // Stereo middel point. Only for visualization
// MapPoints associated to keypoints
std::vector<MapPoint*> mvpMapPoints;
// BoW
KeyFrameDatabase* mpKeyFrameDB;
ORBVocabulary* mpORBvocabulary;
// Grid over the image to speed up feature matching
std::vector< std::vector <std::vector<size_t> > > mGrid;
// Covisibility Graph
std::map<KeyFrame*,int> mConnectedKeyFrameWeights; ///< 与该关键帧连接的关键帧与权重
std::vector<KeyFrame*> mvpOrderedConnectedKeyFrames; ///< 排序后的关键帧
std::vector<int> mvOrderedWeights; ///< 排序后的权重(从大到小)
// Spanning Tree and Loop Edges
bool mbFirstConnection;
KeyFrame* mpParent;
std::set<KeyFrame*> mspChildrens;
std::set<KeyFrame*> mspLoopEdges;
// Bad flags
bool mbNotErase;
bool mbToBeErased;
bool mbBad;
float mHalfBaseline; // Only for visualization
Map* mpMap;
std::mutex mMutexPose;
std::mutex mMutexConnections;
std::mutex mMutexFeatures;
};
} //namespace ORB_SLAM
#endif // KEYFRAME_H
#include "KeyFrame.h"
#include "Converter.h"
#include "ORBmatcher.h"
#include<mutex>
namespace ORB_SLAM2
{
long unsigned int KeyFrame::nNextId=0;
KeyFrame::KeyFrame(Frame &F, Map *pMap, KeyFrameDatabase *pKFDB):
mnFrameId(F.mnId), mTimeStamp(F.mTimeStamp), mnGridCols(FRAME_GRID_COLS), mnGridRows(FRAME_GRID_ROWS),
mfGridElementWidthInv(F.mfGridElementWidthInv), mfGridElementHeightInv(F.mfGridElementHeightInv),
mnTrackReferenceForFrame(0), mnFuseTargetForKF(0), mnBALocalForKF(0), mnBAFixedForKF(0),
mnLoopQuery(0), mnLoopWords(0), mnRelocQuery(0), mnRelocWords(0), mnBAGlobalForKF(0),
fx(F.fx), fy(F.fy), cx(F.cx), cy(F.cy), invfx(F.invfx), invfy(F.invfy),
mbf(F.mbf), mb(F.mb), mThDepth(F.mThDepth), N(F.N), mvKeys(F.mvKeys), mvKeysUn(F.mvKeysUn),
mvuRight(F.mvuRight), mvDepth(F.mvDepth), mDescriptors(F.mDescriptors.clone()),
mBowVec(F.mBowVec), mFeatVec(F.mFeatVec), mnScaleLevels(F.mnScaleLevels), mfScaleFactor(F.mfScaleFactor),
mfLogScaleFactor(F.mfLogScaleFactor), mvScaleFactors(F.mvScaleFactors), mvLevelSigma2(F.mvLevelSigma2),
mvInvLevelSigma2(F.mvInvLevelSigma2), mnMinX(F.mnMinX), mnMinY(F.mnMinY), mnMaxX(F.mnMaxX),
mnMaxY(F.mnMaxY), mK(F.mK), mvpMapPoints(F.mvpMapPoints), mpKeyFrameDB(pKFDB),
mpORBvocabulary(F.mpORBvocabulary), mbFirstConnection(true), mpParent(NULL), mbNotErase(false),
mbToBeErased(false), mbBad(false), mHalfBaseline(F.mb/2), mpMap(pMap)
{
mnId=nNextId++;
mGrid.resize(mnGridCols);
for(int i=0; i<mnGridCols;i++)
{
mGrid[i].resize(mnGridRows);
for(int j=0; j<mnGridRows; j++)
mGrid[i][j] = F.mGrid[i][j];
}
SetPose(F.mTcw);
}
// 计算mBowVec,并且将描述子分散在第4层上
void KeyFrame::ComputeBoW()
{
if(mBowVec.empty() || mFeatVec.empty())
{
vector<cv::Mat> vCurrentDesc = Converter::toDescriptorVector(mDescriptors);
// Feature vector associate features with nodes in the 4th level (from leaves up)
// We assume the vocabulary tree has 6 levels, change the 4 otherwise
mpORBvocabulary->transform(vCurrentDesc,mBowVec,mFeatVec,4);
}
}
// 设置位姿,为了节省计算量,没有直接求逆
// Ow即twc
void KeyFrame::SetPose(const cv::Mat &Tcw_)
{
unique_lock<mutex> lock(mMutexPose);
Tcw_.copyTo(Tcw);
cv::Mat Rcw = Tcw.rowRange(0,3).colRange(0,3);
cv::Mat tcw = Tcw.rowRange(0,3).col(3);
cv::Mat Rwc = Rcw.t();
Ow = -Rwc*tcw;
Twc = cv::Mat::eye(4,4,Tcw.type());
Rwc.copyTo(Twc.rowRange(0,3).colRange(0,3));
Ow.copyTo(Twc.rowRange(0,3).col(3));
cv::Mat center = (cv::Mat_<float>(4,1) << mHalfBaseline, 0 , 0, 1);
Cw = Twc*center;
}
cv::Mat KeyFrame::GetPose()
{
unique_lock<mutex> lock(mMutexPose);
return Tcw.clone();
}
cv::Mat KeyFrame::GetPoseInverse()
{
unique_lock<mutex> lock(mMutexPose);
return Twc.clone();
}
cv::Mat KeyFrame::GetCameraCenter()
{
unique_lock<mutex> lock(mMutexPose);
return Ow.clone();
}
cv::Mat KeyFrame::GetStereoCenter()
{
unique_lock<mutex> lock(mMutexPose);
return Cw.clone();
}
cv::Mat KeyFrame::GetRotation()
{
unique_lock<mutex> lock(mMutexPose);
return Tcw.rowRange(0,3).colRange(0,3).clone();
}
cv::Mat KeyFrame::GetTranslation()
{
unique_lock<mutex> lock(mMutexPose);
return Tcw.rowRange(0,3).col(3).clone();
}
// 为关键帧之间添加连接,如果没有连接,则增加对应的权重;如果该关键帧已经存在但权重不符,修改权重;
// weight 权重,当前关键帧与pKF共同观测到的3d点数量
void KeyFrame::AddConnection(KeyFrame *pKF, const int &weight)
{
{
unique_lock<mutex> lock(mMutexConnections);
if(!mConnectedKeyFrameWeights.count(pKF))
mConnectedKeyFrameWeights[pKF]=weight;
else if(mConnectedKeyFrameWeights[pKF]!=weight)
mConnectedKeyFrameWeights[pKF]=weight;
else
return;
}
UpdateBestCovisibles();
}
// 按照权重对连接的关键帧进行排序
// 每一个关键帧都会维护自己的local map,其中记录了与其他关键帧之间的weight
// 每次为当前关键帧添加新的连接关键帧后,都需要根据weight更新map的结构
void KeyFrame::UpdateBestCovisibles()
{
unique_lock<mutex> lock(mMutexConnections);
vector<pair<int,KeyFrame*> > vPairs;
vPairs.reserve(mConnectedKeyFrameWeights.size());
for(map<KeyFrame*,int>::iterator mit=mConnectedKeyFrameWeights.begin(), mend=mConnectedKeyFrameWeights.end(); mit!=mend; mit++)
vPairs.push_back(make_pair(mit->second,mit->first));
// 按照权重进行排序,默认按升序
sort(vPairs.begin(),vPairs.end());
list<KeyFrame*> lKFs; // keyframe
list<int> lWs; // weight
for(size_t i=0, iend=vPairs.size(); i<iend;i++)
{
// push_front相当于将升序改为降序
lKFs.push_front(vPairs[i].second);
lWs.push_front(vPairs[i].first);
}
mvpOrderedConnectedKeyFrames = vector<KeyFrame*>(lKFs.begin(),lKFs.end());
mvOrderedWeights = vector<int>(lWs.begin(), lWs.end());
}
// 得到与该关键帧连接的关键帧
set<KeyFrame*> KeyFrame::GetConnectedKeyFrames()
{
unique_lock<mutex> lock(mMutexConnections);
set<KeyFrame*> s;
for(map<KeyFrame*,int>::iterator mit=mConnectedKeyFrameWeights.begin();mit!=mConnectedKeyFrameWeights.end();mit++)
s.insert(mit->first);
return s;
}
// 得到与该关键帧连接的关键帧(已按权值排序)
vector<KeyFrame*> KeyFrame::GetVectorCovisibleKeyFrames()
{
unique_lock<mutex> lock(mMutexConnections);
return mvpOrderedConnectedKeyFrames;
}
// 得到与该关键帧共视最好的前N个关键帧
// 如果连接的关键帧少于N,则返回所有连接的关键帧
vector<KeyFrame*> KeyFrame::GetBestCovisibilityKeyFrames(const int &N)
{
unique_lock<mutex> lock(mMutexConnections);
if((int)mvpOrderedConnectedKeyFrames.size()<N)
return mvpOrderedConnectedKeyFrames;
else
return vector<KeyFrame*>(mvpOrderedConnectedKeyFrames.begin(),mvpOrderedConnectedKeyFrames.begin()+N);
}
// 得到与该关键帧连接的权重大于等于w的关键帧
vector<KeyFrame*> KeyFrame::GetCovisiblesByWeight(const int &w)
{
unique_lock<mutex> lock(mMutexConnections);
if(mvpOrderedConnectedKeyFrames.empty())
return vector<KeyFrame*>();
vector<int>::iterator it = upper_bound(mvOrderedWeights.begin(),mvOrderedWeights.end(),w,KeyFrame::weightComp);
if(it==mvOrderedWeights.end() && *mvOrderedWeights.rbegin()<w)
return vector<KeyFrame*>();
else
{
int n = it-mvOrderedWeights.begin();
return vector<KeyFrame*>(mvpOrderedConnectedKeyFrames.begin(), mvpOrderedConnectedKeyFrames.begin()+n);
}
}
// 得到指定帧和当前帧之间的权重
int KeyFrame::GetWeight(KeyFrame *pKF)
{
unique_lock<mutex> lock(mMutexConnections);
// 先判断是否有连接
if(mConnectedKeyFrameWeights.count(pKF))
return mConnectedKeyFrameWeights[pKF];
else
return 0;
}
// 增加地图点
void KeyFrame::AddMapPoint(MapPoint *pMP, const size_t &idx)
{
unique_lock<mutex> lock(mMutexFeatures);
mvpMapPoints[idx]=pMP;
}
void KeyFrame::EraseMapPointMatch(const size_t &idx)
{
unique_lock<mutex> lock(mMutexFeatures);
mvpMapPoints[idx]=static_cast<MapPoint*>(NULL);
}
void KeyFrame::EraseMapPointMatch(MapPoint* pMP)
{
int idx = pMP->GetIndexInKeyFrame(this);
if(idx>=0)
mvpMapPoints[idx]=static_cast<MapPoint*>(NULL);
}
// 替换对应idx的地图点
void KeyFrame::ReplaceMapPointMatch(const size_t &idx, MapPoint* pMP)
{
mvpMapPoints[idx]=pMP;
}
// 得到当前关键帧中的地图点
set<MapPoint*> KeyFrame::GetMapPoints()
{
unique_lock<mutex> lock(mMutexFeatures);
set<MapPoint*> s;
for(size_t i=0, iend=mvpMapPoints.size(); i<iend; i++)
{
if(!mvpMapPoints[i])
continue;
MapPoint* pMP = mvpMapPoints[i];
if(!pMP->isBad())
s.insert(pMP);
}
return s;
}
// 返回能被至少minObs个相机观测到的地图点的个数
// 即高质量地图点的数量
int KeyFrame::TrackedMapPoints(const int &minObs)
{
unique_lock<mutex> lock(mMutexFeatures);
int nPoints=0;
const bool bCheckObs = minObs>0;
for(int i=0; i<N; i++)
{
MapPoint* pMP = mvpMapPoints[i];
if(pMP)
{
if(!pMP->isBad())
{
if(bCheckObs)
{
// 该MapPoint是一个高质量的MapPoint
if(mvpMapPoints[i]->Observations()>=minObs)
nPoints++;
}
else
nPoints++;
}
}
}
return nPoints;
}
vector<MapPoint*> KeyFrame::GetMapPointMatches()
{
unique_lock<mutex> lock(mMutexFeatures);
return mvpMapPoints;
}
// 获得指定的地图点
MapPoint* KeyFrame::GetMapPoint(const size_t &idx)
{
unique_lock<mutex> lock(mMutexFeatures);
return mvpMapPoints[idx];
}
/**
* 1. 首先获得该关键帧的所有MapPoint点,统计观测到这些3d点的每个关键与其它所有关键帧之间的共视程度
* 对每一个找到的关键帧,建立一条边,边的权重是该关键帧与当前关键帧共同观测的3d点的个数
* 2. 并且该权重必须大于一个阈值,如果没有超过该阈值的权重,那么就只保留权重最大的边
* 3. 对这些连接按照权重从大到小进行排序
*/
void KeyFrame::UpdateConnections()
{
// 这个函数可以更新关键帧之间的连接关系
map<KeyFrame*,int> KFcounter; // 关键帧-权重,权重为其它关键帧与当前关键帧共视3d点的个数
vector<MapPoint*> vpMP;
{
unique_lock<mutex> lockMPs(mMutexFeatures);
vpMP = mvpMapPoints;
}
//For all map points in keyframe check in which other keyframes are they seen
//Increase counter for those keyframes
// 统计每一个关键帧都有多少关键帧与它存在共视关系,统计结果放在KFcounter
for(vector<MapPoint*>::iterator vit=vpMP.begin(), vend=vpMP.end(); vit!=vend; vit++)
{
MapPoint* pMP = *vit;
if(!pMP)
continue;
if(pMP->isBad())
continue;
// observations记录了可以观测到该MapPoint的所有关键帧
map<KeyFrame*,size_t> observations = pMP->GetObservations();
for(map<KeyFrame*,size_t>::iterator mit=observations.begin(), mend=observations.end(); mit!=mend; mit++)
{
// 除去自身
if(mit->first->mnId==mnId)
continue;
KFcounter[mit->first]++;
}
}
// This should not happen
if(KFcounter.empty())
return;
// If the counter is greater than threshold add connection
// In case no keyframe counter is over threshold add the one with maximum counter
int nmax=0;
KeyFrame* pKFmax=NULL;
int th = 15;
// vPairs记录与其它关键帧共视帧数大于th的关键帧
vector<pair<int,KeyFrame*> > vPairs;
vPairs.reserve(KFcounter.size());
for(map<KeyFrame*,int>::iterator mit=KFcounter.begin(), mend=KFcounter.end(); mit!=mend; mit++)
{
if(mit->second>nmax)
{
nmax=mit->second;
// 找到对应权重最大的关键帧
pKFmax=mit->first;
}
if(mit->second>=th)
{
// 对应权重大于阈值,对这些关键帧建立连接
vPairs.push_back(make_pair(mit->second,mit->first));
// 更新KFcounter中该关键帧的mConnectedKeyFrameWeights
// 更新其它KeyFrame的mConnectedKeyFrameWeights,更新其它关键帧与当前帧的连接权重
(mit->first)->AddConnection(this,mit->second);
}
}
// 如果没有超过阈值的权重,则对权重最大的关键帧建立连接
if(vPairs.empty())
{
vPairs.push_back(make_pair(nmax,pKFmax));
pKFmax->AddConnection(this,nmax);
}
// vPairs里存的都是相互共视程度比较高的关键帧和共视权重
sort(vPairs.begin(),vPairs.end());
list<KeyFrame*> lKFs;
list<int> lWs;
for(size_t i=0; i<vPairs.size();i++)
{
// 降序
lKFs.push_front(vPairs[i].second);
lWs.push_front(vPairs[i].first);
}
{
unique_lock<mutex> lockCon(mMutexConnections);
// mspConnectedKeyFrames = spConnectedKeyFrames;
// 更新图的连接
mvpOrderedConnectedKeyFrames = vector<KeyFrame*>(lKFs.begin(),lKFs.end());
mvOrderedWeights = vector<int>(lWs.begin(), lWs.end());
// 更新生成树的连接
if(mbFirstConnection && mnId!=0)
{
// 初始化该关键帧的父关键帧为共视程度最高的那个关键帧
mpParent = mvpOrderedConnectedKeyFrames.front();
mpParent->AddChild(this);
mbFirstConnection = false;
}
}
}
void KeyFrame::AddChild(KeyFrame *pKF)
{
unique_lock<mutex> lockCon(mMutexConnections);
mspChildrens.insert(pKF);
}
void KeyFrame::EraseChild(KeyFrame *pKF)
{
unique_lock<mutex> lockCon(mMutexConnections);
mspChildrens.erase(pKF);
}
void KeyFrame::ChangeParent(KeyFrame *pKF)
{
unique_lock<mutex> lockCon(mMutexConnections);
mpParent = pKF;
pKF->AddChild(this);
}
set<KeyFrame*> KeyFrame::GetChilds()
{
unique_lock<mutex> lockCon(mMutexConnections);
return mspChildrens;
}
KeyFrame* KeyFrame::GetParent()
{
unique_lock<mutex> lockCon(mMutexConnections);
return mpParent;
}
bool KeyFrame::hasChild(KeyFrame *pKF)
{
unique_lock<mutex> lockCon(mMutexConnections);
return mspChildrens.count(pKF);
}
void KeyFrame::AddLoopEdge(KeyFrame *pKF)
{
unique_lock<mutex> lockCon(mMutexConnections);
mbNotErase = true;
mspLoopEdges.insert(pKF);
}
set<KeyFrame*> KeyFrame::GetLoopEdges()
{
unique_lock<mutex> lockCon(mMutexConnections);
return mspLoopEdges;
}
void KeyFrame::SetNotErase()
{
unique_lock<mutex> lock(mMutexConnections);
mbNotErase = true;
}
void KeyFrame::SetErase()
{
{
unique_lock<mutex> lock(mMutexConnections);
if(mspLoopEdges.empty())
{
mbNotErase = false;
}
}
if(mbToBeErased)
{
SetBadFlag();
}
}
// 删除关键帧时,首先要检测mspLoopEdges是否是空的
// 因为如果当前帧维护了一个回环,删了这个关键帧回环没有了,则不能删除掉
// 所以通常情况下是空的,就可以把mbNotErase设置成false
// 也就是说当前帧是可删除的
void KeyFrame::SetBadFlag()
{
{
unique_lock<mutex> lock(mMutexConnections);
if(mnId==0)
return;
else if(mbNotErase)
{
mbToBeErased = true;
return;
}
}
for(map<KeyFrame*,int>::iterator mit = mConnectedKeyFrameWeights.begin(), mend=mConnectedKeyFrameWeights.end(); mit!=mend; mit++)
mit->first->EraseConnection(this); // 让其它的关键帧删除与自己的联系
for(size_t i=0; i<mvpMapPoints.size(); i++)
if(mvpMapPoints[i])
mvpMapPoints[i]->EraseObservation(this);// 让与自己有联系的MapPoint删除与自己的联系
{
unique_lock<mutex> lock(mMutexConnections);
unique_lock<mutex> lock1(mMutexFeatures);
//清空自己与其它关键帧之间的联系
mConnectedKeyFrameWeights.clear();
mvpOrderedConnectedKeyFrames.clear();
// Update Spanning Tree
set<KeyFrame*> sParentCandidates;
sParentCandidates.insert(mpParent);
// Assign at each iteration one children with a parent (the pair with highest covisibility weight)
// Include that children as new parent candidate for the rest
// 如果这个关键帧有自己的子关键帧,则让子关键帧找新的父关键帧
while(!mspChildrens.empty())
{
bool bContinue = false;
int max = -1;
KeyFrame* pC;
KeyFrame* pP;
for(set<KeyFrame*>::iterator sit=mspChildrens.begin(), send=mspChildrens.end(); sit!=send; sit++)
{
KeyFrame* pKF = *sit;
if(pKF->isBad())
continue;
// Check if a parent candidate is connected to the keyframe
// 子关键帧遍历每一个与它相连的关键帧(共视关键帧)
vector<KeyFrame*> vpConnected = pKF->GetVectorCovisibleKeyFrames();
for(size_t i=0, iend=vpConnected.size(); i<iend; i++)
{
for(set<KeyFrame*>::iterator spcit=sParentCandidates.begin(), spcend=sParentCandidates.end(); spcit!=spcend; spcit++)
{
if(vpConnected[i]->mnId == (*spcit)->mnId)
{
int w = pKF->GetWeight(vpConnected[i]);
if(w>max)
{
pC = pKF;
pP = vpConnected[i];
max = w;
bContinue = true;
}
}
}
}
}
if(bContinue)
{
// 子节点找到了新的父节点,子节点更新自己的父节点
pC->ChangeParent(pP);
// 那么该子节点升级,作为其它子节点的备选父节点
sParentCandidates.insert(pC);
mspChildrens.erase(pC);
}
else
break;
}
// If a children has no covisibility links with any parent candidate, assign to the original parent of this KF
// 如果还有子节点没有找到新的父节点
if(!mspChildrens.empty())
for(set<KeyFrame*>::iterator sit=mspChildrens.begin(); sit!=mspChildrens.end(); sit++)
{
// 直接把父节点的父节点作为自己的父节点
(*sit)->ChangeParent(mpParent);
}
mpParent->EraseChild(this);
mTcp = Tcw*mpParent->GetPoseInverse();
mbBad = true;
}
mpMap->EraseKeyFrame(this);
mpKeyFrameDB->erase(this);
}
bool KeyFrame::isBad()
{
unique_lock<mutex> lock(mMutexConnections);
return mbBad;
}
void KeyFrame::EraseConnection(KeyFrame* pKF)
{
bool bUpdate = false;
{
unique_lock<mutex> lock(mMutexConnections);
if(mConnectedKeyFrameWeights.count(pKF))
{
mConnectedKeyFrameWeights.erase(pKF);
bUpdate=true;
}
}
if(bUpdate)
UpdateBestCovisibles();
}
// r为边长(半径)
vector<size_t> KeyFrame::GetFeaturesInArea(const float &x, const float &y, const float &r) const
{
vector<size_t> vIndices;
vIndices.reserve(N);
const int nMinCellX = max(0,(int)floor((x-mnMinX-r)*mfGridElementWidthInv));
if(nMinCellX>=mnGridCols)
return vIndices;
const int nMaxCellX = min((int)mnGridCols-1,(int)ceil((x-mnMinX+r)*mfGridElementWidthInv));
if(nMaxCellX<0)
return vIndices;
const int nMinCellY = max(0,(int)floor((y-mnMinY-r)*mfGridElementHeightInv));
if(nMinCellY>=mnGridRows)
return vIndices;
const int nMaxCellY = min((int)mnGridRows-1,(int)ceil((y-mnMinY+r)*mfGridElementHeightInv));
if(nMaxCellY<0)
return vIndices;
for(int ix = nMinCellX; ix<=nMaxCellX; ix++)
{
for(int iy = nMinCellY; iy<=nMaxCellY; iy++)
{
const vector<size_t> vCell = mGrid[ix][iy];
for(size_t j=0, jend=vCell.size(); j<jend; j++)
{
const cv::KeyPoint &kpUn = mvKeysUn[vCell[j]];
const float distx = kpUn.pt.x-x;
const float disty = kpUn.pt.y-y;
if(fabs(distx)<r && fabs(disty)<r)
vIndices.push_back(vCell[j]);
}
}
}
return vIndices;
}
bool KeyFrame::IsInImage(const float &x, const float &y) const
{
return (x>=mnMinX && x<mnMaxX && y>=mnMinY && y<mnMaxY);
}
cv::Mat KeyFrame::UnprojectStereo(int i)
{
const float z = mvDepth[i];
if(z>0)
{
// 由2维图像反投影到相机坐标系
const float u = mvKeys[i].pt.x;
const float v = mvKeys[i].pt.y;
const float x = (u-cx)*z*invfx;
const float y = (v-cy)*z*invfy;
cv::Mat x3Dc = (cv::Mat_<float>(3,1) << x, y, z);
unique_lock<mutex> lock(mMutexPose);
// 由相机坐标系转换到世界坐标系
// Twc为相机坐标系到世界坐标系的变换矩阵
return Twc.rowRange(0,3).colRange(0,3)*x3Dc+Twc.rowRange(0,3).col(3);
}
else
return cv::Mat();
}
// 计算场景中中间的深度
float KeyFrame::ComputeSceneMedianDepth(const int q)
{
vector<MapPoint*> vpMapPoints;
cv::Mat Tcw_;
{
unique_lock<mutex> lock(mMutexFeatures);
unique_lock<mutex> lock2(mMutexPose);
vpMapPoints = mvpMapPoints;
Tcw_ = Tcw.clone();
}
vector<float> vDepths;
vDepths.reserve(N);
cv::Mat Rcw2 = Tcw_.row(2).colRange(0,3);
Rcw2 = Rcw2.t();
float zcw = Tcw_.at<float>(2,3);
for(int i=0; i<N; i++)
{
if(mvpMapPoints[i])
{
MapPoint* pMP = mvpMapPoints[i];
cv::Mat x3Dw = pMP->GetWorldPos();
float z = Rcw2.dot(x3Dw)+zcw;
vDepths.push_back(z);
}
}
sort(vDepths.begin(),vDepths.end());
return vDepths[(vDepths.size()-1)/q];
}
} //namespace ORB_SLAM
KeyFrame是SLAM中的关键的帧,对于恢复地图非常重要,关键帧由普通帧构造,什么样的普通帧、以及什么时候插入关键帧,在tracking模块中实现。在关键帧类中有几个重要的函数
1.为关键帧之间添加连接 UpdateConnections()
每个关键帧,都和自己周围的几个一起能观测到某些地图点的关键帧共同构成一个小的图,图之间的连接的权重就是相互之间共同观测到的地图点的个数,每个关键帧都会维护自己的一个小的图,记录和谁(关键帧)有共视关系,共视程度是多少,因此,每当为当前关键帧添加新的连接关键帧后都要根据权重对相应的连接结构进行调整。使用 UpdateConnections() 函数。具体的事说,该函数首先获取当前帧的所有地图点,然后获取所有能观测到该点的关键帧,之后进行统计,即统计了当前帧和其他帧的共视点的个数,如果和某个帧的共视点数大于阈值,则两帧之间建立连接关系。
2. UpdateBestCovisibles() 函数
该函数按照权重对上一步构成连接关系的帧进行排序,更新相应的成员变量。每当添加关键帧之间的连接后、删除关键帧间的连接关系都会调用该函数更新。
3. SetErase() 更新父子结点关系
每个关键帧维护的图中的节点是关键帧,其间有父子关系,有时候需要删除一些关键帧,那么就要处理好节点之间的关系,否则会造成图的破坏。具体的函数是SetErase(),做法如下
(1) 将当前帧this的父节点添加到候选父节点中;
(2)遍历this的儿子节点,再对每个儿子节点遍历其共视帧;
(3)如果某个儿子的共视帧正好是在候选父节点中,那么直接将该儿子的父节点指定为那个候选父亲;
(4)对于找到新父节点的节点,将其升级为候选父节点,作为其他节点的备选父节点;
(5)如果一遍下来还有儿子节点没有找到新的父节点,那么直接把this节点的父节点作为这个儿子节点的父节点,即交给“爷爷”去管了;
总之:删除一个关键帧,需要判断该帧是否维护了一个闭环,如果维护了一个闭环的话那么不能删除;如果没有维护闭环则可以删除;
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