Remove .bat files, actually finish rename this time

1 files changed, 352 insertions, 0 deletions

diff --git a/ftnoir_tracker_pt/point_tracker.cpp b/ftnoir_tracker_pt/point_tracker.cpp
new file mode 100644
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+++ b/ftnoir_tracker_pt/point_tracker.cpp
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+/* Copyright (c) 2012 Patrick Ruoff

+ *

+ * Permission to use, copy, modify, and/or distribute this software for any

+ * purpose with or without fee is hereby granted, provided that the above

+ * copyright notice and this permission notice appear in all copies.

+ */

+

+#include "point_tracker.h"

+

+#include <vector>

+#include <algorithm>

+#include <cmath>

+

+#include <QDebug>

+

+using namespace cv;

+using namespace boost;

+using namespace std;

+

+const float PI = 3.14159265358979323846f;

+

+// ----------------------------------------------------------------------------

+static void get_row(const Matx33f& m, int i, Vec3f& v)

+{

+	v[0] = m(i,0);

+	v[1] = m(i,1);

+	v[2] = m(i,2);

+}

+

+static void set_row(Matx33f& m, int i, const Vec3f& v)

+{

+	m(i,0) = v[0];

+	m(i,1) = v[1];

+	m(i,2) = v[2];

+}

+

+// ----------------------------------------------------------------------------

+PointModel::PointModel(Vec3f M01, Vec3f M02)

+	: M01(M01), M02(M02)

+{	

+	// calculate u

+	u = M01.cross(M02);

+	u /= norm(u);

+

+	// calculate projection matrix on M01,M02 plane

+	float s11 = M01.dot(M01);

+	float s12 = M01.dot(M02);

+	float s22 = M02.dot(M02);

+	P = 1.0/(s11*s22-s12*s12) * Matx22f(s22, -s12, 

+		                               -s12,  s11);

+

+	// calculate d and d_order for simple freetrack-like point correspondence

+	vector<Vec2f> points;

+	points.push_back(Vec2f(0,0));

+	points.push_back(Vec2f(M01[0], M01[1]));

+	points.push_back(Vec2f(M02[0], M02[1]));

+	// fit line to orthographically projected points

+	// ERROR: yields wrong results with colinear points?!

+	/*

+	Vec4f line;

+	fitLine(points, line, CV_DIST_L2, 0, 0.01, 0.01);

+	d[0] = line[0]; d[1] = line[1];

+	*/

+	// TODO: fix this

+	d = Vec2f(M01[0]-M02[0], M01[1]-M02[1]);

+

+	// sort model points

+	get_d_order(points, d_order);

+}

+

+void PointModel::get_d_order(const std::vector<cv::Vec2f>& points, int d_order[]) const

+{

+	// get sort indices with respect to d scalar product

+	vector< pair<float,int> > d_vals;

+	for (int i = 0; i<points.size(); ++i)

+		d_vals.push_back(pair<float, int>(d.dot(points[i]), i));

+

+	struct

+	{

+		bool operator()(const pair<float, int>& a, const pair<float, int>& b) { return a.first < b.first; }

+	} comp;

+	sort(d_vals.begin(), d_vals.end(), comp);

+

+	for (int i = 0; i<points.size(); ++i)

+		d_order[i] = d_vals[i].second;

+}

+

+

+// ----------------------------------------------------------------------------

+PointTracker::PointTracker() : init_phase(true), dt_valid(0), dt_reset(1), v_t(0,0,0), v_r(0,0,0), dynamic_pose_resolution(true)

+{

+	X_CM.t[2] = 1000;	// default position: 1 m away from cam;

+}

+

+void PointTracker::reset()

+{

+	// enter init phase and reset velocities

+	init_phase = true;

+	dt_valid = 0;

+	reset_velocities();

+}

+

+void PointTracker::reset_velocities()

+{	

+	v_t = Vec3f(0,0,0);

+	v_r = Vec3f(0,0,0);

+}

+

+

+bool PointTracker::track(const vector<Vec2f>& points, float f, float dt)

+{

+	if (!dynamic_pose_resolution) init_phase = true;

+

+	dt_valid += dt;

+	// if there was no valid tracking result for too long, do a reset

+	if (dt_valid > dt_reset) 

+	{

+		//qDebug()<<"dt_valid "<<dt_valid<<" > dt_reset "<<dt_reset;

+		reset();

+	}

+

+	// if there is a pointtracking problem, reset the velocities

+	if (!point_model || points.size() != PointModel::N_POINTS) 

+	{

+		//qDebug()<<"Wrong number of points!";

+		reset_velocities();

+		return false;

+	}

+

+	X_CM_old = X_CM;	// backup old transformation for velocity calculation

+

+	if (!init_phase) 

+		predict(dt_valid);

+

+	// if there is a point correspondence problem something has gone wrong, do a reset

+	if (!find_correspondences(points, f))

+	{

+		//qDebug()<<"Error in finding point correspondences!";

+		X_CM = X_CM_old;	// undo prediction

+		reset();

+		return false;

+	}

+

+	int n_iter = POSIT(f);

+	//qDebug()<<"Number of POSIT iterations: "<<n_iter;

+

+	if (!init_phase)

+		update_velocities(dt_valid);

+

+	// we have a valid tracking result, leave init phase and reset time since valid result

+	init_phase = false;

+	dt_valid = 0;

+	return true;

+}

+

+void PointTracker::predict(float dt)

+{

+	// predict with constant velocity

+	Matx33f R;

+	Rodrigues(dt*v_r, R);

+	X_CM.R = R*X_CM.R;

+	X_CM.t += dt * v_t;

+}

+

+void PointTracker::update_velocities(float dt)

+{

+	// update velocities

+	Rodrigues(X_CM.R*X_CM_old.R.t(), v_r);

+	v_r /= dt;

+	v_t = (X_CM.t - X_CM_old.t)/dt;

+}

+

+bool PointTracker::find_correspondences(const vector<Vec2f>& points, float f)

+{

+	if (init_phase) {

+		// We do a simple freetrack-like sorting in the init phase...

+		// sort points

+		int point_d_order[PointModel::N_POINTS];

+		point_model->get_d_order(points, point_d_order);

+

+		// set correspondences

+		for (int i=0; i<PointModel::N_POINTS; ++i)

+		{

+			p[point_model->d_order[i]] = points[point_d_order[i]];

+		}

+	}

+	else {

+		// ... otherwise we look at the distance to the projection of the expected model points 

+		// project model points under current pose

+		p_exp[0] = project(Vec3f(0,0,0), f);

+		p_exp[1] = project(point_model->M01, f);

+		p_exp[2] = project(point_model->M02, f);

+

+		// set correspondences by minimum distance to projected model point

+		bool point_taken[PointModel::N_POINTS];

+		for (int i=0; i<PointModel::N_POINTS; ++i)

+			point_taken[i] = false;

+

+		float min_sdist = 0;

+		int min_idx = 0;

+		

+		for (int i=0; i<PointModel::N_POINTS; ++i)

+		{

+			// find closest point to projected model point i

+			for (int j=0; j<PointModel::N_POINTS; ++j)

+			{

+				Vec2f d = p_exp[i]-points[j];

+				float sdist = d.dot(d);

+				if (sdist < min_sdist || j==0) 

+				{

+					min_idx = j;

+					min_sdist = sdist;

+				}

+			}

+			// if one point is closest to more than one model point, abort

+			if (point_taken[min_idx]) return false;

+			point_taken[min_idx] = true;

+			p[i] = points[min_idx];

+		}

+	}

+	return true;

+}

+

+

+

+int PointTracker::POSIT(float f)

+{

+	// POSIT algorithm for coplanar points as presented in

+	// [Denis Oberkampf, Daniel F. DeMenthon, Larry S. Davis: "Iterative Pose Estimation Using Coplanar Feature Points"]

+	// we use the same notation as in the paper here

+

+	// The expected rotation used for resolving the ambiguity in POSIT:

+	// In every iteration step the rotation closer to R_expected is taken 

+	Matx33f R_expected;	

+	if (init_phase)

+		R_expected = Matx33f::eye(); // in the init phase, we want to be close to the default pose = no rotation

+	else 

+		R_expected = X_CM.R; // later we want to be close to the last (predicted) rotation

+	

+	// initial pose = last (predicted) pose

+	Vec3f k;

+	get_row(X_CM.R, 2, k);

+	float Z0 = X_CM.t[2];

+

+	float old_epsilon_1 = 0;

+	float old_epsilon_2 = 0;

+	float epsilon_1 = 1;

+	float epsilon_2 = 1;

+

+	Vec3f I0, J0;

+	Vec2f I0_coeff, J0_coeff;

+

+	Vec3f I_1, J_1, I_2, J_2;

+	Matx33f R_1, R_2;

+	Matx33f* R_current;

+

+	const int MAX_ITER = 100;

+	const float EPS_THRESHOLD = 1e-4;

+

+	int i=1;

+	for (; i<MAX_ITER; ++i)

+	{

+		epsilon_1 = k.dot(point_model->M01)/Z0;

+		epsilon_2 = k.dot(point_model->M02)/Z0;

+

+		// vector of scalar products <I0, M0i> and <J0, M0i>

+		Vec2f I0_M0i(p[1][0]*(1.0 + epsilon_1) - p[0][0], 

+			         p[2][0]*(1.0 + epsilon_2) - p[0][0]);

+		Vec2f J0_M0i(p[1][1]*(1.0 + epsilon_1) - p[0][1],

+			         p[2][1]*(1.0 + epsilon_2) - p[0][1]);

+

+		// construct projection of I, J onto M0i plane: I0 and J0

+		I0_coeff = point_model->P * I0_M0i;

+		J0_coeff = point_model->P * J0_M0i;

+		I0 = I0_coeff[0]*point_model->M01 + I0_coeff[1]*point_model->M02;

+		J0 = J0_coeff[0]*point_model->M01 + J0_coeff[1]*point_model->M02;

+

+		// calculate u component of I, J		

+		float II0 = I0.dot(I0);

+		float IJ0 = I0.dot(J0);

+		float JJ0 = J0.dot(J0);

+		float rho, theta;

+		if (JJ0 == II0) {

+			rho = sqrt(abs(2*IJ0));

+			theta = -PI/4;

+			if (IJ0<0) theta *= -1;

+		}

+		else {

+			rho = sqrt(sqrt( (JJ0-II0)*(JJ0-II0) + 4*IJ0*IJ0 ));

+			theta = atan( -2*IJ0 / (JJ0-II0) );

+			if (JJ0 - II0 < 0) theta += PI;

+			theta /= 2;

+		}

+

+		// construct the two solutions

+		I_1 = I0 + rho*cos(theta)*point_model->u;	

+		I_2 = I0 - rho*cos(theta)*point_model->u;

+

+		J_1 = J0 + rho*sin(theta)*point_model->u;

+		J_2 = J0 - rho*sin(theta)*point_model->u;

+

+		float norm_const = 1.0/norm(I_1); // all have the same norm

+		

+		// create rotation matrices

+		I_1 *= norm_const; J_1 *= norm_const;

+		I_2 *= norm_const; J_2 *= norm_const;

+

+		set_row(R_1, 0, I_1);

+		set_row(R_1, 1, J_1);

+		set_row(R_1, 2, I_1.cross(J_1));

+		

+		set_row(R_2, 0, I_2);

+		set_row(R_2, 1, J_2);

+		set_row(R_2, 2, I_2.cross(J_2));

+

+		// the single translation solution

+		Z0 = norm_const * f;

+

+		// pick the rotation solution closer to the expected one

+		// in simple metric d(A,B) = || I - A * B^T ||

+		float R_1_deviation = norm(Matx33f::eye() - R_expected * R_1.t());

+		float R_2_deviation = norm(Matx33f::eye() - R_expected * R_2.t());

+

+		if (R_1_deviation < R_2_deviation)

+			R_current = &R_1;

+		else

+			R_current = &R_2;

+

+		get_row(*R_current, 2, k);

+

+		// check for convergence condition

+		if (abs(epsilon_1 - old_epsilon_1) +  abs(epsilon_2 - old_epsilon_2) < EPS_THRESHOLD)

+			break;

+		old_epsilon_1 = epsilon_1;

+		old_epsilon_2 = epsilon_2;

+	}	

+

+	// apply results

+	X_CM.R = *R_current;

+	X_CM.t[0] = p[0][0] * Z0/f;

+	X_CM.t[1] = p[0][1] * Z0/f;

+	X_CM.t[2] = Z0;

+

+	return i;

+

+	//Rodrigues(X_CM.R, r);

+	//qDebug()<<"iter: "<<i;

+	//qDebug()<<"t: "<<X_CM.t[0]<<' '<<X_CM.t[1]<<' '<<X_CM.t[2];

+	//Vec3f r;

+	//

+	//qDebug()<<"r: "<<r[0]<<' '<<r[1]<<' '<<r[2]<<'\n';

+}