2021SC@SDUSC
KeyFrame中有一个很重要的概念共视图1.首先解释一下什么是共视图（mConnectedKeyFrameWeights）：能看到同一地图点的两关键帧之间存在共视关系,共视地图点的数量被称为权重.
2.共视图结构由3个成员变量维护:
mConnectedKeyFrameWeights是一个std::map,无序地保存当前关键帧的共视关键帧及权重.
mvpOrderedConnectedKeyFrames和mvOrderedWeights按权重降序分别保存当前关键帧的共视关键帧列表和权重列表.
3.下面解释几个有关关键帧的成员函数
void KeyFrame::AddConnection(KeyFrame *pKF, const int &weight) {// step1. 修改变量mConnectedKeyFrameWeights { unique_lock<mutex> lock(mMutexConnections); if (!mConnectedKeyFrameWeights.count(pKF) || mConnectedKeyFrameWeights[pKF] != weight) mConnectedKeyFrameWeights[pKF] = weight; else return; } // step2. 调用函数UpdateBestCovisibles()修改变量mvpOrderedConnectedKeyFrames和mvOrderedWeights UpdateBestCovisibles();}在map<KeyFrame*,int> mConnectedKeyFrameWeights容器中加入此关键帧；
对mConnectedKeyFrameWeights中存储的关键帧集按照连接权重进行降序排序，排序之后的关键帧存储到mvpOrderedConnectedKeyFrames中，排序后的关键帧存储到mvOrderedWeights中
2）将关联的关键帧进行排序
void KeyFrame::UpdateBestCovisibles() { unique_lock<mutex> lock(mMutexConnections); // 取出所有关键帧进行排序,排序结果存入变量mvpOrderedConnectedKeyFrames和mvOrderedWeights中 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)); sort(vPairs.begin(), vPairs.end()); list<KeyFrame *> lKFs; list<int> lWs; for (size_t i = 0, iend = vPairs.size(); i < iend; i++) { 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());}对mConnectedKeyFrameWeights中存储的关键帧集按照连接权重进行降序排序，排序之后的关键帧存储到mvpOrderedConnectedKeyFrames中，排序后的关键帧存储到mvOrderedWeights中
3）返回关联关键帧（关联关键帧是指权重大于15的共视关键帧）
set<KeyFrame*> KeyFrame::GetConnectedKeyFrames()抽取mConnectedKeyFrameWeights容器中存储的关键帧集返回
4）更新连接，创建共视图
void KeyFrame::UpdateConnections() { // 第一步. 通过遍历当前帧地图点获取其与其它关键帧的共视程度,存入变量KFcounter中 vector<MapPoint *> vpMP; { unique_lock<mutex> lockMPs(mMutexFeatures); vpMP = mvpMapPoints; } map<KeyFrame *, int> KFcounter; for (MapPoint *pMP : vpMP) { map<KeyFrame *, size_t> observations = pMP->GetObservations(); for (map<KeyFrame *, size_t>::iterator mit = observations.begin(); mit != observations.end(); mit++) { if (mit->first->mnId == mnId)// 与当前关键帧本身不算共视 continue; KFcounter[mit->first]++; } } // 第二步. 找到与当前关键帧共视程度超过15的关键帧,存入变量vPairs中 vector<pair<int, KeyFrame *> > vPairs; int th = 15; int nmax = 0; KeyFrame *pKFmax = NULL; for (map<KeyFrame *, int>::iterator mit = KFcounter.begin(), mend = KFcounter.end(); mit != mend; mit++) { if (mit->second > nmax) { nmax = mit->second; pKFmax = mit->first; } if (mit->second >= th) { vPairs.push_back(make_pair(mit->second, mit->first)); (mit->first)->AddConnection(this, mit->second);// 对超过阈值的共视边建立连接 } } // 第三步. 对关键帧按照共视权重降序排序,存入变量mvpOrderedConnectedKeyFrames和mvOrderedWeights中 sort(vPairs.begin(), vPairs.end()); list<KeyFrame *> lKFs; list<int> lWs; for (size_t i = 0; i < vPairs.size(); i++) { lKFs.push_front(vPairs[i].second); lWs.push_front(vPairs[i].first); } { unique_lock<mutex> lockCon(mMutexConnections); mConnectedKeyFrameWeights = KFcounter; mvpOrderedConnectedKeyFrames = vector<KeyFrame *>(lKFs.begin(), lKFs.end()); mvOrderedWeights = vector<int>(lWs.begin(), lWs.end()); // 第四步. 对于第一次加入生成树的关键帧,取共视程度最高的关键帧为父关键帧 if (mbFirstConnection && mnId != 0) { mpParent = mvpOrderedConnectedKeyFrames.front(); mpParent->AddChild(this); mbFirstConnection = false; } }}