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Tracker.cc
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// Copyright 2008 Isis Innovation Limited
#include "OpenGL.h"
#include "Tracker.h"
#include "MEstimator.h"
#include "ShiTomasi.h"
#include "SmallMatrixOpts.h"
#include "PatchFinder.h"
#include "TrackerData.h"
#include <cvd/utility.h>
#include <cvd/gl_helpers.h>
#include <cvd/fast_corner.h>
#include <cvd/vision.h>
#include <TooN/wls.h>
#include <gvars3/instances.h>
#include <gvars3/GStringUtil.h>
#include <fstream>
#include <fcntl.h>
namespace PTAMM {
using namespace CVD;
using namespace std;
using namespace GVars3;
/**
* The constructor mostly sets up interal reference variables to the other classes..
* @param irVideoSize video image size
* @param c camera model
* @param maps list of maps
* @param m current map
* @param mm map maker
*/
Tracker::Tracker(ImageRef irVideoSize, const ATANCamera &c, std::vector<Map*> &maps, Map *m, MapMaker &mm) :
mCurrentKF(c),
mvpMaps(maps),
mpMap(m),
mMapMaker(mm),
mCamera(c),
mRelocaliser(maps, mCamera),
mirSize(irVideoSize),
mFirstKF(mCamera),
mPreviousFrameKF(mCamera)
{
mCurrentKF.bFixed = false;
GUI.RegisterCommand("Reset", GUICommandCallBack, this);
// GUI.RegisterCommand("KeyPress", GUICommandCallBack, this);
GUI.RegisterCommand("PokeTracker", GUICommandCallBack, this);
TrackerData::irImageSize = mirSize;
mpSBILastFrame = NULL;
mpSBIThisFrame = NULL;
// Most of the initialisation is done in Reset()
Reset();
}
/**
* Common reset code for Reset() and ResetAll()
*/
void Tracker::ResetCommon()
{
mbDidCoarse = false;
mbUserPressedSpacebar = false;
mTrackingQuality = GOOD;
mnLostFrames = 0;
mdMSDScaledVelocityMagnitude = 0;
mCurrentKF.dSceneDepthMean = 1.0;
mCurrentKF.dSceneDepthSigma = 1.0;
mnInitialStage = TRAIL_TRACKING_NOT_STARTED;
mlTrails.clear();
mCamera.SetImageSize(mirSize);
mCurrentKF.mMeasurements.clear();
mnLastKeyFrameDropped = -20;
mnFrame=0;
mv6CameraVelocity = Zeros;
mbJustRecoveredSoUseCoarse = false;
}
/**
* Resets the tracker, wipes the map.
* This is the main Reset-handler-entry-point of the program!
* Other classes' resets propagate from here.
* It's always called in the Tracker's thread, often as a GUI command.
*/
void Tracker::Reset()
{
if( mpMap->bEditLocked ) {
cerr << "MAP LOCKED: Cannot reset map " << mpMap->MapID() << "." << endl;
return;
}
ResetCommon();
// Tell the MapMaker to reset itself..
// this may take some time, since the mapmaker thread may have to wait
// for an abort-check during calculation, so sleep while waiting.
// MapMaker will also clear the map.
mMapMaker.RequestReset();
while(!mMapMaker.ResetDone())
#ifndef WIN32
usleep(10);
#else
Sleep(1);
#endif
}
// TrackFrame is called by System.cc with each incoming video frame.
// It figures out what state the tracker is in, and calls appropriate internal tracking
// functions. bDraw tells the tracker wether it should output any GL graphics
// or not (it should not draw, for example, when AR stuff is being shown.)
void Tracker::TrackFrame(Image<CVD::byte> &imFrame, bool bDraw)
{
mbDraw = bDraw;
mMessageForUser.str(""); // Wipe the user message clean
// Take the input video image, and convert it into the tracker's keyframe struct
// This does things like generate the image pyramid and find FAST corners
mCurrentKF.mMeasurements.clear();
mCurrentKF.MakeKeyFrame_Lite(imFrame);
// Update the small images for the rotation estimator
static gvar3<double> gvdSBIBlur("Tracker.RotationEstimatorBlur", 0.75, SILENT);
static gvar3<int> gvnUseSBI("Tracker.UseRotationEstimator", 1, SILENT);
mbUseSBIInit = *gvnUseSBI;
if(!mpSBIThisFrame)
{
mpSBIThisFrame = new SmallBlurryImage(mCurrentKF, *gvdSBIBlur);
mpSBILastFrame = new SmallBlurryImage(mCurrentKF, *gvdSBIBlur);
}
else
{
delete mpSBILastFrame;
mpSBILastFrame = mpSBIThisFrame;
mpSBIThisFrame = new SmallBlurryImage(mCurrentKF, *gvdSBIBlur);
}
// From now on we only use the keyframe struct!
mnFrame++;
if(mbDraw)
{
glDrawPixels(mCurrentKF.aLevels[0].im);
if(GV2.GetInt("Tracker.DrawFASTCorners",0, SILENT))
{
glColor3f(1,0,1); glPointSize(1); glBegin(GL_POINTS);
for(unsigned int i=0; i<mCurrentKF.aLevels[0].vCorners.size(); i++)
glVertex(mCurrentKF.aLevels[0].vCorners[i]);
glEnd();
}
}
// Decide what to do - if there is a map, try to track the map ...
if(mpMap->IsGood())
{
if(mnLostFrames < NUM_LOST_FRAMES) // .. but only if we're not lost!
{
if(mbUseSBIInit)
CalcSBIRotation();
ApplyMotionModel(); //
TrackMap(); // These three lines do the main tracking work.
UpdateMotionModel(); //
AssessTrackingQuality(); // Check if we're lost or if tracking is poor.
{ // Provide some feedback for the user:
mMessageForUser << "Tracking Map, quality ";
if(mTrackingQuality == GOOD) mMessageForUser << "good.";
if(mTrackingQuality == DODGY) mMessageForUser << "poor.";
if(mTrackingQuality == BAD) mMessageForUser << "bad.";
mMessageForUser << " Found:";
for(int i=0; i<LEVELS; i++) {
mMessageForUser << " " << manMeasFound[i] << "/" << manMeasAttempted[i];
}
mMessageForUser << " Map " << mpMap->MapID() << ": "
<< mpMap->vpPoints.size() << "P, " << mpMap->vpKeyFrames.size() << "KF";
}
// Heuristics to check if a key-frame should be added to the map:
if(mTrackingQuality == GOOD &&
mMapMaker.NeedNewKeyFrame(mCurrentKF) &&
mnFrame - mnLastKeyFrameDropped > 20 &&
mpMap->QueueSize() < 3)
{
mMessageForUser << " Adding key-frame.";
AddNewKeyFrame();
};
}
else // what if there is a map, but tracking has been lost?
{
mMessageForUser << "** Attempting recovery **.";
if(AttemptRecovery())
{
TrackMap();
AssessTrackingQuality();
}
}
if(mbDraw)
RenderGrid();
}
else // If there is no map, try to make one.
TrackForInitialMap();
// GUI interface
while(!mvQueuedCommands.empty())
{
GUICommandHandler(mvQueuedCommands.begin()->sCommand, mvQueuedCommands.begin()->sParams);
mvQueuedCommands.erase(mvQueuedCommands.begin());
}
};
/**
* Try to relocalise in case tracking was lost.
* Returns success or failure as a bool.
* Actually, the SBI relocaliser will almost always return true, even if
* it has no idea where it is, so graphics will go a bit
* crazy when lost. Could use a tighter SSD threshold and return more false,
* but the way it is now gives a snappier response and I prefer it.
* @return success
*/
bool Tracker::AttemptRecovery()
{
bool bRelocGood = mRelocaliser.AttemptRecovery( *mpMap, mCurrentKF );
if(!bRelocGood)
return false;
SE3<> se3Best = mRelocaliser.BestPose();
mse3CamFromWorld = mse3StartPos = se3Best;
mv6CameraVelocity = Zeros;
mbJustRecoveredSoUseCoarse = true;
return true;
}
/**
* Draw the reference grid to give the user an idea of wether tracking is OK or not.
*/
void Tracker::RenderGrid()
{
// The colour of the ref grid shows if the coarse stage of tracking was used
// (it's turned off when the camera is sitting still to reduce jitter.)
if(mbDidCoarse)
glColor4f(0.0f, 0.5f, 0.0f, 0.6f);
else
glColor4f(0.0f,0.0f,0.0f,0.6f);
// The grid is projected manually, i.e. GL receives projected 2D coords to draw.
int nHalfCells = 8;
int nTot = nHalfCells * 2 + 1;
Image<Vector<2> > imVertices(ImageRef(nTot,nTot));
for(int i=0; i<nTot; i++)
for(int j=0; j<nTot; j++)
{
Vector<3> v3;
v3[0] = (i - nHalfCells) * 0.1;
v3[1] = (j - nHalfCells) * 0.1;
v3[2] = 0.0;
Vector<3> v3Cam = mse3CamFromWorld * v3;
if(v3Cam[2] < 0.001)
v3Cam[2] = 0.001;
imVertices[i][j] = mCamera.Project(project(v3Cam));
}
glEnable(GL_LINE_SMOOTH);
glEnable(GL_BLEND);
glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA);
glLineWidth(2);
for(int i=0; i<nTot; i++)
{
glBegin(GL_LINE_STRIP);
for(int j=0; j<nTot; j++)
glVertex(imVertices[i][j]);
glEnd();
glBegin(GL_LINE_STRIP);
for(int j=0; j<nTot; j++)
glVertex(imVertices[j][i]);
glEnd();
};
glLineWidth(1);
glColor3f(1,0,0);
}
/**
* GUI interface. Stuff commands onto the back of a queue so the tracker handles
* them in its own thread at the end of each frame. Note the charming lack of
* any thread safety (no lock on mvQueuedCommands).
* @param ptr object pointer
* @param sCommand command string
* @param sParams parameter string
*/
void Tracker::GUICommandCallBack(void* ptr, string sCommand, string sParams)
{
Command c;
c.sCommand = sCommand;
c.sParams = sParams;
((Tracker*) ptr)->mvQueuedCommands.push_back(c);
}
/**
* This is called in the tracker's own thread.
* @param sCommand command string
* @param sParams parameter string
*/
void Tracker::GUICommandHandler(string sCommand, string sParams) // Called by the callback func..
{
if(sCommand=="Reset")
{
Reset();
return;
}
else if((sCommand=="PokeTracker"))
{
mbUserPressedSpacebar = true;
return;
}
cout << "! Tracker::GUICommandHandler: unhandled command "<< sCommand << endl;
exit(1);
}
/**
* Handle a key press command
* This is a change from PTAM to enable games to use keys
* @param sKey the key pressed
* @return true if the key was used.
*/
bool Tracker::HandleKeyPress( string sKey )
{
// KeyPress commands are issued by GLWindow, and passed to Tracker via System
if(sKey == "Space")
{
mbUserPressedSpacebar = true;
return true;
}
else if(sKey == "r")
{
Reset();
return true;
}
return false;
}
/**
* Routine for establishing the initial map. This requires two spacebar presses from the user
* to define the first two key-frames. Salient points are tracked between the two keyframes
* using cheap frame-to-frame tracking (which is very brittle - quick camera motion will
* break it.) The salient points are stored in a list of `Trail' data structures.
* What action TrackForInitialMap() takes depends on the mnInitialStage enum variable..
*/
void Tracker::TrackForInitialMap()
{
// MiniPatch tracking threshhold.
static gvar3<int> gvnMaxSSD("Tracker.MiniPatchMaxSSD", 100000, SILENT);
MiniPatch::mnMaxSSD = *gvnMaxSSD;
// What stage of initial tracking are we at?
if(mnInitialStage == TRAIL_TRACKING_NOT_STARTED)
{
if(mbUserPressedSpacebar) // First spacebar = this is the first keyframe
{
mbUserPressedSpacebar = false;
TrailTracking_Start();
mnInitialStage = TRAIL_TRACKING_STARTED;
}
else
mMessageForUser << "Point camera at planar scene and press spacebar to start tracking for initial map.";
return;
};
if(mnInitialStage == TRAIL_TRACKING_STARTED)
{
int nGoodTrails = TrailTracking_Advance(); // This call actually tracks the trails
if(nGoodTrails < 10) // if most trails have been wiped out, no point continuing.
{
Reset();
return;
}
// If the user pressed spacebar here, use trails to run stereo and make the intial map..
if(mbUserPressedSpacebar)
{
mbUserPressedSpacebar = false;
vector<pair<ImageRef, ImageRef> > vMatches; // This is the format the mapmaker wants for the stereo pairs
for(list<Trail>::iterator i = mlTrails.begin(); i!=mlTrails.end(); i++)
vMatches.push_back(pair<ImageRef, ImageRef>(i->irInitialPos,
i->irCurrentPos));
mMapMaker.InitFromStereo(mFirstKF, mCurrentKF, vMatches, mse3CamFromWorld); // This will take some time!
mnInitialStage = TRAIL_TRACKING_COMPLETE;
}
else
mMessageForUser << "Translate the camera slowly sideways, and press spacebar again to perform stereo init.";
}
}
/**
* The current frame is to be the first keyframe!
*/
void Tracker::TrailTracking_Start()
{
mCurrentKF.MakeKeyFrame_Rest(); // This populates the Candidates list, which is Shi-Tomasi thresholded.
mFirstKF = mCurrentKF;
vector<pair<double,ImageRef> > vCornersAndSTScores;
for(unsigned int i=0; i<mCurrentKF.aLevels[0].vCandidates.size(); i++) // Copy candidates into a trivially sortable vector
{ // so that we can choose the image corners with max ST score
Candidate &c = mCurrentKF.aLevels[0].vCandidates[i];
if(!mCurrentKF.aLevels[0].im.in_image_with_border(c.irLevelPos, MiniPatch::mnHalfPatchSize))
continue;
vCornersAndSTScores.push_back(pair<double,ImageRef>(-1.0 * c.dSTScore, c.irLevelPos)); // negative so highest score first in sorted list
};
sort(vCornersAndSTScores.begin(), vCornersAndSTScores.end()); // Sort according to Shi-Tomasi score
int nToAdd = GV2.GetInt("MaxInitialTrails", 1000, SILENT);
for(unsigned int i = 0; i<vCornersAndSTScores.size() && nToAdd > 0; i++)
{
if(!mCurrentKF.aLevels[0].im.in_image_with_border(vCornersAndSTScores[i].second, MiniPatch::mnHalfPatchSize))
continue;
Trail t;
t.mPatch.SampleFromImage(vCornersAndSTScores[i].second, mCurrentKF.aLevels[0].im);
t.irInitialPos = vCornersAndSTScores[i].second;
t.irCurrentPos = t.irInitialPos;
mlTrails.push_back(t);
nToAdd--;
}
mPreviousFrameKF = mFirstKF; // Always store the previous frame so married-matching can work.
}
/**
* Steady-state trail tracking: Advance from the previous frame, remove duds.
* @return number of good trails
*/
int Tracker::TrailTracking_Advance()
{
int nGoodTrails = 0;
if(mbDraw)
{
glPointSize(5);
glLineWidth(2);
glEnable(GL_POINT_SMOOTH);
glEnable(GL_LINE_SMOOTH);
glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA);
glEnable(GL_BLEND);
glBegin(GL_LINES);
}
MiniPatch BackwardsPatch;
Level &lCurrentFrame = mCurrentKF.aLevels[0];
Level &lPreviousFrame = mPreviousFrameKF.aLevels[0];
for(list<Trail>::iterator i = mlTrails.begin(); i!=mlTrails.end();)
{
list<Trail>::iterator next = i; next++;
Trail &trail = *i;
ImageRef irStart = trail.irCurrentPos;
ImageRef irEnd = irStart;
bool bFound = trail.mPatch.FindPatch(irEnd, lCurrentFrame.im, 10, lCurrentFrame.vCorners);
if(bFound)
{
// Also find backwards in a married-matches check
BackwardsPatch.SampleFromImage(irEnd, lCurrentFrame.im);
ImageRef irBackWardsFound = irEnd;
bFound = BackwardsPatch.FindPatch(irBackWardsFound, lPreviousFrame.im, 10, lPreviousFrame.vCorners);
if((irBackWardsFound - irStart).mag_squared() > 2)
bFound = false;
trail.irCurrentPos = irEnd;
nGoodTrails++;
}
if(mbDraw)
{
if(!bFound)
glColor3f(0,1,1); // Failed trails flash purple before dying.
else
glColor3f(1,1,0);
glVertex(trail.irInitialPos);
if(bFound) glColor3f(1,0,0);
glVertex(trail.irCurrentPos);
}
if(!bFound) // Erase from list of trails if not found this frame.
{
mlTrails.erase(i);
}
i = next;
}
if(mbDraw)
glEnd();
mPreviousFrameKF = mCurrentKF;
return nGoodTrails;
}
/**
* TrackMap is the main purpose of the Tracker.
* It first projects all map points into the image to find a potentially-visible-set (PVS);
* Then it tries to find some points of the PVS in the image;
* Then it updates camera pose according to any points found.
* Above may happen twice if a coarse tracking stage is performed.
* Finally it updates the tracker's current-frame-KeyFrame struct with any
* measurements made.
* A lot of low-level functionality is split into helper classes:
* class TrackerData handles the projection of a MapPoint and stores intermediate results;
* class PatchFinder finds a projected MapPoint in the current-frame-KeyFrame.
*/
void Tracker::TrackMap()
{
// Some accounting which will be used for tracking quality assessment:
for(int i=0; i<LEVELS; i++)
manMeasAttempted[i] = manMeasFound[i] = 0;
// The Potentially-Visible-Set (PVS) is split into pyramid levels.
vector<TrackerData*> avPVS[LEVELS];
for(int i=0; i<LEVELS; i++)
avPVS[i].reserve(500);
// For all points in the map..
for(unsigned int i=0; i<mpMap->vpPoints.size(); i++)
{
MapPoint &p= *(mpMap->vpPoints[i]);
// Ensure that this map point has an associated TrackerData struct.
if(!p.pTData) p.pTData = new TrackerData(&p);
TrackerData &TData = *p.pTData;
// Project according to current view, and if it's not in the image, skip.
TData.Project(mse3CamFromWorld, mCamera);
if(!TData.bInImage)
continue;
// Calculate camera projection derivatives of this point.
TData.GetDerivsUnsafe(mCamera);
// And check what the PatchFinder (included in TrackerData) makes of the mappoint in this view..
TData.nSearchLevel = TData.Finder.CalcSearchLevelAndWarpMatrix(TData.Point, mse3CamFromWorld, TData.m2CamDerivs);
if(TData.nSearchLevel == -1)
continue; // a negative search pyramid level indicates an inappropriate warp for this view, so skip.
// Otherwise, this point is suitable to be searched in the current image! Add to the PVS.
TData.bSearched = false;
TData.bFound = false;
avPVS[TData.nSearchLevel].push_back(&TData);
};
// Next: A large degree of faffing about and deciding which points are going to be measured!
// First, randomly shuffle the individual levels of the PVS.
for(int i=0; i<LEVELS; i++)
random_shuffle(avPVS[i].begin(), avPVS[i].end());
// The next two data structs contain the list of points which will next
// be searched for in the image, and then used in pose update.
vector<TrackerData*> vNextToSearch;
vector<TrackerData*> vIterationSet;
// Tunable parameters to do with the coarse tracking stage:
static gvar3<unsigned int> gvnCoarseMin("Tracker.CoarseMin", 20, SILENT); // Min number of large-scale features for coarse stage
static gvar3<unsigned int> gvnCoarseMax("Tracker.CoarseMax", 60, SILENT); // Max number of large-scale features for coarse stage
static gvar3<unsigned int> gvnCoarseRange("Tracker.CoarseRange", 30, SILENT); // Pixel search radius for coarse features
static gvar3<int> gvnCoarseSubPixIts("Tracker.CoarseSubPixIts", 8, SILENT); // Max sub-pixel iterations for coarse features
static gvar3<int> gvnCoarseDisabled("Tracker.DisableCoarse", 0, SILENT); // Set this to 1 to disable coarse stage (except after recovery)
static gvar3<double> gvdCoarseMinVel("Tracker.CoarseMinVelocity", 0.006, SILENT); // Speed above which coarse stage is used.
unsigned int nCoarseMax = *gvnCoarseMax;
unsigned int nCoarseRange = *gvnCoarseRange;
mbDidCoarse = false;
// Set of heuristics to check if we should do a coarse tracking stage.
bool bTryCoarse = true;
if(*gvnCoarseDisabled ||
mdMSDScaledVelocityMagnitude < *gvdCoarseMinVel ||
nCoarseMax == 0)
bTryCoarse = false;
if(mbJustRecoveredSoUseCoarse)
{
bTryCoarse = true;
nCoarseMax *=2;
nCoarseRange *=2;
mbJustRecoveredSoUseCoarse = false;
};
// If we do want to do a coarse stage, also check that there's enough high-level
// PV map points. We use the lowest-res two pyramid levels (LEVELS-1 and LEVELS-2),
// with preference to LEVELS-1.
if(bTryCoarse && avPVS[LEVELS-1].size() + avPVS[LEVELS-2].size() > *gvnCoarseMin )
{
// Now, fill the vNextToSearch struct with an appropriate number of
// TrackerDatas corresponding to coarse map points! This depends on how many
// there are in different pyramid levels compared to CoarseMin and CoarseMax.
if(avPVS[LEVELS-1].size() <= nCoarseMax)
{ // Fewer than CoarseMax in LEVELS-1? then take all of them, and remove them from the PVS list.
vNextToSearch = avPVS[LEVELS-1];
avPVS[LEVELS-1].clear();
}
else
{ // ..otherwise choose nCoarseMax at random, again removing from the PVS list.
for(unsigned int i=0; i<nCoarseMax; i++)
vNextToSearch.push_back(avPVS[LEVELS-1][i]);
avPVS[LEVELS-1].erase(avPVS[LEVELS-1].begin(), avPVS[LEVELS-1].begin() + nCoarseMax);
}
// If didn't source enough from LEVELS-1, get some from LEVELS-2... same as above.
if(vNextToSearch.size() < nCoarseMax)
{
unsigned int nMoreCoarseNeeded = nCoarseMax - vNextToSearch.size();
if(avPVS[LEVELS-2].size() <= nMoreCoarseNeeded)
{
vNextToSearch = avPVS[LEVELS-2];
avPVS[LEVELS-2].clear();
}
else
{
for(unsigned int i=0; i<nMoreCoarseNeeded; i++)
vNextToSearch.push_back(avPVS[LEVELS-2][i]);
avPVS[LEVELS-2].erase(avPVS[LEVELS-2].begin(), avPVS[LEVELS-2].begin() + nMoreCoarseNeeded);
}
}
// Now go and attempt to find these points in the image!
unsigned int nFound = SearchForPoints(vNextToSearch, nCoarseRange, *gvnCoarseSubPixIts);
vIterationSet = vNextToSearch; // Copy over into the to-be-optimised list.
if(nFound >= *gvnCoarseMin) // Were enough found to do any meaningful optimisation?
{
mbDidCoarse = true;
for(int iter = 0; iter<10; iter++) // If so: do ten Gauss-Newton pose updates iterations.
{
if(iter != 0)
{ // Re-project the points on all but the first iteration.
for(unsigned int i=0; i<vIterationSet.size(); i++)
if(vIterationSet[i]->bFound)
vIterationSet[i]->ProjectAndDerivs(mse3CamFromWorld, mCamera);
}
for(unsigned int i=0; i<vIterationSet.size(); i++)
if(vIterationSet[i]->bFound)
vIterationSet[i]->CalcJacobian();
double dOverrideSigma = 0.0;
// Hack: force the MEstimator to be pretty brutal
// with outliers beyond the fifth iteration.
if(iter > 5)
dOverrideSigma = 1.0;
// Calculate and apply the pose update...
Vector<6> v6Update =
CalcPoseUpdate(vIterationSet, dOverrideSigma);
mse3CamFromWorld = SE3<>::exp(v6Update) * mse3CamFromWorld;
};
}
};
// So, at this stage, we may or may not have done a coarse tracking stage.
// Now do the fine tracking stage. This needs many more points!
int nFineRange = 10; // Pixel search range for the fine stage.
if(mbDidCoarse) // Can use a tighter search if the coarse stage was already done.
nFineRange = 5;
// What patches shall we use this time? The high-level ones are quite important,
// so do all of these, with sub-pixel refinement.
{
int l = LEVELS - 1;
for(unsigned int i=0; i<avPVS[l].size(); i++)
avPVS[l][i]->ProjectAndDerivs(mse3CamFromWorld, mCamera);
SearchForPoints(avPVS[l], nFineRange, 8);
for(unsigned int i=0; i<avPVS[l].size(); i++)
vIterationSet.push_back(avPVS[l][i]); // Again, plonk all searched points onto the (maybe already populate) vIterationSet.
};
// All the others levels: Initially, put all remaining potentially visible patches onto vNextToSearch.
vNextToSearch.clear();
for(int l=LEVELS - 2; l>=0; l--)
for(unsigned int i=0; i<avPVS[l].size(); i++)
vNextToSearch.push_back(avPVS[l][i]);
// But we haven't got CPU to track _all_ patches in the map - arbitrarily limit
// ourselves to 1000, and choose these randomly.
static gvar3<int> gvnMaxPatchesPerFrame("Tracker.MaxPatchesPerFrame", 1000, SILENT);
int nFinePatchesToUse = *gvnMaxPatchesPerFrame - static_cast<int>(vIterationSet.size());
if((int) vNextToSearch.size() > nFinePatchesToUse)
{
random_shuffle(vNextToSearch.begin(), vNextToSearch.end());
vNextToSearch.resize(nFinePatchesToUse); // Chop!
};
// If we did a coarse tracking stage: re-project and find derivs of fine points
if(mbDidCoarse)
for(unsigned int i=0; i<vNextToSearch.size(); i++)
vNextToSearch[i]->ProjectAndDerivs(mse3CamFromWorld, mCamera);
// Find fine points in image:
SearchForPoints(vNextToSearch, nFineRange, 0);
// And attach them all to the end of the optimisation-set.
for(unsigned int i=0; i<vNextToSearch.size(); i++)
vIterationSet.push_back(vNextToSearch[i]);
// Again, ten gauss-newton pose update iterations.
Vector<6> v6LastUpdate;
v6LastUpdate = Zeros;
for(int iter = 0; iter<10; iter++)
{
bool bNonLinearIteration; // For a bit of time-saving: don't do full nonlinear
// reprojection at every iteration - it really isn't necessary!
if(iter == 0 || iter == 4 || iter == 9)
bNonLinearIteration = true; // Even this is probably overkill, the reason we do many
else // iterations is for M-Estimator convergence rather than
bNonLinearIteration = false; // linearisation effects.
if(iter != 0) // Either way: first iteration doesn't need projection update.
{
if(bNonLinearIteration)
{
for(unsigned int i=0; i<vIterationSet.size(); i++)
if(vIterationSet[i]->bFound)
vIterationSet[i]->ProjectAndDerivs(mse3CamFromWorld, mCamera);
}
else
{
for(unsigned int i=0; i<vIterationSet.size(); i++)
if(vIterationSet[i]->bFound)
vIterationSet[i]->LinearUpdate(v6LastUpdate);
};
}
if(bNonLinearIteration)
for(unsigned int i=0; i<vIterationSet.size(); i++)
if(vIterationSet[i]->bFound)
vIterationSet[i]->CalcJacobian();
// Again, an M-Estimator hack beyond the fifth iteration.
double dOverrideSigma = 0.0;
if(iter > 5)
dOverrideSigma = 16.0;
// Calculate and update pose; also store update vector for linear iteration updates.
Vector<6> v6Update =
CalcPoseUpdate(vIterationSet, dOverrideSigma, iter==9);
mse3CamFromWorld = SE3<>::exp(v6Update) * mse3CamFromWorld;
v6LastUpdate = v6Update;
};
if(mbDraw)
{
glPointSize(6);
glEnable(GL_BLEND);
glEnable(GL_POINT_SMOOTH);
glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA);
glBegin(GL_POINTS);
for(vector<TrackerData*>::reverse_iterator it = vIterationSet.rbegin();
it!= vIterationSet.rend();
it++)
{
if(! (*it)->bFound)
continue;
glColor(gavLevelColors[(*it)->nSearchLevel]);
glVertex((*it)->v2Image);
}
glEnd();
glDisable(GL_BLEND);
}
// Update the current keyframe with info on what was found in the frame.
// Strictly speaking this is unnecessary to do every frame, it'll only be
// needed if the KF gets added to MapMaker. Do it anyway.
// Export pose to current keyframe:
mCurrentKF.se3CfromW = mse3CamFromWorld;
// Record successful measurements. Use the KeyFrame-Measurement struct for this.
mCurrentKF.mMeasurements.clear();
for(vector<TrackerData*>::iterator it = vIterationSet.begin();
it!= vIterationSet.end();
it++)
{
if(! (*it)->bFound)
continue;
Measurement m;
m.v2RootPos = (*it)->v2Found;
m.v2ImplanePos = mCamera.UnProject(m.v2RootPos);
m.m2CamDerivs = mCamera.GetProjectionDerivs();
m.nLevel = (*it)->nSearchLevel;
m.bSubPix = (*it)->bDidSubPix;
mCurrentKF.mMeasurements[& ((*it)->Point)] = m;
}
// Finally, find the mean scene depth from tracked features
{
double dSum = 0;
double dSumSq = 0;
int nNum = 0;
for(vector<TrackerData*>::iterator it = vIterationSet.begin();
it!= vIterationSet.end();
it++)
if((*it)->bFound)
{
double z = (*it)->v3Cam[2];
dSum+= z;
dSumSq+= z*z;
nNum++;
};
if(nNum > 20)
{
mCurrentKF.dSceneDepthMean = dSum/nNum;
mCurrentKF.dSceneDepthSigma = sqrt((dSumSq / nNum) - (mCurrentKF.dSceneDepthMean) * (mCurrentKF.dSceneDepthMean));
}
}
}
/**
* Find points in the image. Uses the PatchFiner struct stored in TrackerData
* @param vTD tracker data
* @param nRange search range
* @param nSubPixIts number of sub-pixel iterations required
* @return number of points found
*/
int Tracker::SearchForPoints(vector<TrackerData*> &vTD, int nRange, int nSubPixIts)
{
int nFound = 0;
for(unsigned int i=0; i<vTD.size(); i++) // for each point..
{
// First, attempt a search at pixel locations which are FAST corners.
// (PatchFinder::FindPatchCoarse)
TrackerData &TD = *vTD[i];
PatchFinder &Finder = TD.Finder;
Finder.MakeTemplateCoarseCont(TD.Point);
if(Finder.TemplateBad())
{
TD.bInImage = TD.bPotentiallyVisible = TD.bFound = false;
continue;
}
manMeasAttempted[Finder.GetLevel()]++; // Stats for tracking quality assessmenta
bool bFound =
Finder.FindPatchCoarse(ir(TD.v2Image), mCurrentKF, nRange);
TD.bSearched = true;
if(!bFound)
{
TD.bFound = false;
continue;
}
TD.bFound = true;
TD.dSqrtInvNoise = (1.0 / Finder.GetLevelScale());
nFound++;
manMeasFound[Finder.GetLevel()]++;
// Found the patch in coarse search - are Sub-pixel iterations wanted too?
if(nSubPixIts > 0)
{
TD.bDidSubPix = true;
Finder.MakeSubPixTemplate();
bool bSubPixConverges=Finder.IterateSubPixToConvergence(mCurrentKF, nSubPixIts);
if(!bSubPixConverges)
{ // If subpix doesn't converge, the patch location is probably very dubious!
TD.bFound = false;
nFound--;
manMeasFound[Finder.GetLevel()]--;
continue;
}
TD.v2Found = Finder.GetSubPixPos();
}
else
{
TD.v2Found = Finder.GetCoarsePosAsVector();
TD.bDidSubPix = false;
}
}
return nFound;
};
/**
* Calculate a pose update 6-vector from a bunch of image measurements.
* User-selectable M-Estimator.
* Normally this robustly estimates a sigma-squared for all the measurements
* to reduce outlier influence, but this can be overridden if
* dOverrideSigma is positive. Also, bMarkOutliers set to true
* records any instances of a point being marked an outlier measurement
* by the Tukey MEstimator.
* @param vTD tracker data
* @param dOverrideSigma
* @param bMarkOutliers
* @return
*/
Vector<6> Tracker::CalcPoseUpdate(vector<TrackerData*> vTD, double dOverrideSigma, bool bMarkOutliers)
{
// Which M-estimator are we using?
int nEstimator = 0;
static gvar3<string> gvsEstimator("TrackerMEstimator", "Tukey", SILENT);
if(*gvsEstimator == "Tukey")
nEstimator = 0;
else if(*gvsEstimator == "Cauchy")
nEstimator = 1;
else if(*gvsEstimator == "Huber")
nEstimator = 2;
else
{
cout << "Invalid TrackerMEstimator, choices are Tukey, Cauchy, Huber" << endl;
nEstimator = 0;
*gvsEstimator = "Tukey";
};
// Find the covariance-scaled reprojection error for each measurement.
// Also, store the square of these quantities for M-Estimator sigma squared estimation.
vector<double> vdErrorSquared;
for(unsigned int f=0; f<vTD.size(); f++)
{
TrackerData &TD = *vTD[f];
if(!TD.bFound)
continue;
TD.v2Error_CovScaled = TD.dSqrtInvNoise* (TD.v2Found - TD.v2Image);
vdErrorSquared.push_back(TD.v2Error_CovScaled * TD.v2Error_CovScaled);
};
// No valid measurements? Return null update.
if(vdErrorSquared.size() == 0)
return makeVector( 0,0,0,0,0,0);
// What is the distribution of errors?
double dSigmaSquared;
if(dOverrideSigma > 0)
dSigmaSquared = dOverrideSigma; // Bit of a waste having stored the vector of square errors in this case!
else
{
if (nEstimator == 0)
dSigmaSquared = Tukey::FindSigmaSquared(vdErrorSquared);
else if(nEstimator == 1)
dSigmaSquared = Cauchy::FindSigmaSquared(vdErrorSquared);
else
dSigmaSquared = Huber::FindSigmaSquared(vdErrorSquared);
}
// The TooN WLSCholesky class handles reweighted least squares.
// It just needs errors and jacobians.
WLS<6> wls;
wls.add_prior(100.0); // Stabilising prior
for(unsigned int f=0; f<vTD.size(); f++)
{
TrackerData &TD = *vTD[f];
if(!TD.bFound)
continue;
Vector<2> &v2 = TD.v2Error_CovScaled;
double dErrorSq = v2 * v2;
double dWeight;
if(nEstimator == 0)
dWeight= Tukey::Weight(dErrorSq, dSigmaSquared);
else if(nEstimator == 1)
dWeight= Cauchy::Weight(dErrorSq, dSigmaSquared);
else
dWeight= Huber::Weight(dErrorSq, dSigmaSquared);
// Inlier/outlier accounting, only really works for cut-off estimators such as Tukey.
if(dWeight == 0.0)
{
if(bMarkOutliers)
TD.Point.nMEstimatorOutlierCount++;
continue;
}
else
if(bMarkOutliers)
TD.Point.nMEstimatorInlierCount++;
Matrix<2,6> &m26Jac = TD.m26Jacobian;
wls.add_mJ(v2[0], TD.dSqrtInvNoise * m26Jac[0], dWeight); // These two lines are currently
wls.add_mJ(v2[1], TD.dSqrtInvNoise * m26Jac[1], dWeight); // the slowest bit of poseits
}
wls.compute();
return wls.get_mu();
}
/**
* Just add the current velocity to the current pose.
* N.b. this doesn't actually use time in any way, i.e. it assumes
* a one-frame-per-second camera. Skipped frames etc
* are not handled properly here.
*/
void Tracker::ApplyMotionModel()
{
mse3StartPos = mse3CamFromWorld;
Vector<6> v6Velocity = mv6CameraVelocity;
if(mbUseSBIInit)
{
v6Velocity.slice<3,3>() = mv6SBIRot.slice<3,3>();
v6Velocity[0] = 0.0;
v6Velocity[1] = 0.0;
}
mse3CamFromWorld = SE3<>::exp(v6Velocity) * mse3StartPos;
};