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Consensus.cpp
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Consensus.cpp
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#include "Consensus.h"
#define _USE_MATH_DEFINES //Necessary for M_PI to be available on Windows
#include <cmath>
#include "fastcluster/fastcluster.h"
using std::max_element;
using std::distance;
namespace cmt {
void Consensus::initialize(const vector<Point2f> & points_normalized)
{
FILE_LOG(logDEBUG) << "Consensus::initialize() call";
//Copy normalized points
this->points_normalized = points_normalized;
size_t num_points = points_normalized.size();
//Create matrices of pairwise distances/angles
distances_pairwise = Mat(num_points, num_points, CV_32FC1);
angles_pairwise = Mat(num_points, num_points, CV_32FC1);
for (size_t i = 0; i < num_points; i++)
{
for (size_t j = 0; j < num_points; j++)
{
Point2f v = points_normalized[i] - points_normalized[j];
float distance = norm(v);
float angle = atan2(v.y,v.x);
distances_pairwise.at<float>(i,j) = distance;
angles_pairwise.at<float>(i,j) = angle;
}
}
FILE_LOG(logDEBUG) << "Consensus::initialize() return";
}
//TODO: Check for estimate_scale, estimate_rotation
void Consensus::estimateScaleRotation(const vector<Point2f> & points, const vector<int> & classes,
float & scale, float & rotation)
{
FILE_LOG(logDEBUG) << "Consensus::estimateScaleRotation() call";
//Compute pairwise changes in scale/rotation
vector<float> changes_scale;
if (estimate_scale) changes_scale.reserve(points.size()*points.size());
vector<float> changes_angles;
if (estimate_rotation) changes_angles.reserve(points.size()*points.size());
for (size_t i = 0; i < points.size(); i++)
{
for (size_t j = 0; j < points.size(); j++)
{
if (classes[i] != classes[j])
{
Point2f v = points[i] - points[j];
if (estimate_scale)
{
float distance = norm(v);
float distance_original = distances_pairwise.at<float>(classes[i],classes[j]);
float change_scale = distance / distance_original;
changes_scale.push_back(change_scale);
}
if (estimate_rotation)
{
float angle = atan2(v.y,v.x);
float angle_original = angles_pairwise.at<float>(classes[i],classes[j]);
float change_angle = angle - angle_original;
//Fix long way angles
if (fabs(change_angle) > M_PI) {
change_angle = sgn(change_angle) * 2 * M_PI + change_angle;
}
changes_angles.push_back(change_angle);
}
}
}
}
//Do not use changes_scale, changes_angle after this point as their order is changed by median()
if (changes_scale.size() < 2) scale = 1;
else scale = median(changes_scale);
if (changes_angles.size() < 2) rotation = 0;
else rotation = median(changes_angles);
FILE_LOG(logDEBUG) << "Consensus::estimateScaleRotation() return";
}
void Consensus::findConsensus(const vector<Point2f> & points, const vector<int> & classes,
const float scale, const float rotation,
Point2f & center, vector<Point2f> & points_inlier, vector<int> & classes_inlier)
{
FILE_LOG(logDEBUG) << "Consensus::findConsensus() call";
//If no points are available, reteurn nan
if (points.size() == 0)
{
center.x = numeric_limits<float>::quiet_NaN();
center.y = numeric_limits<float>::quiet_NaN();
FILE_LOG(logDEBUG) << "Consensus::findConsensus() return";
return;
}
//Compute votes
vector<Point2f> votes(points.size());
for (size_t i = 0; i < points.size(); i++)
{
votes[i] = points[i] - scale * rotate(points_normalized[classes[i]], rotation);
}
t_index N = points.size();
float * D = new float[N*(N-1)/2]; //This is a lot of memory, so we put it on the heap
cluster_result Z(N-1);
//Compute pairwise distances between votes
int index = 0;
for (size_t i = 0; i < points.size(); i++)
{
for (size_t j = i+1; j < points.size(); j++)
{
//TODO: This index calculation is correct, but is it a good thing?
//int index = i * (points.size() - 1) - (i*i + i) / 2 + j - 1;
D[index] = norm(votes[i] - votes[j]);
index++;
}
}
FILE_LOG(logDEBUG) << "Consensus::MST_linkage_core() call";
MST_linkage_core(N,D,Z);
FILE_LOG(logDEBUG) << "Consensus::MST_linkage_core() return";
union_find nodes(N);
//Sort linkage by distance ascending
std::stable_sort(Z[0], Z[N-1]);
//S are cluster sizes
int * S = new int[2*N-1];
//TODO: Why does this loop go to 2*N-1? Shouldn't it be simply N? Everything > N gets overwritten later
for(int i = 0; i < 2*N-1; i++)
{
S[i] = 1;
}
t_index parent = 0; //After the loop ends, parent contains the index of the last cluster
for (node const * NN=Z[0]; NN!=Z[N-1]; ++NN)
{
// Get two data points whose clusters are merged in step i.
// Find the cluster identifiers for these points.
t_index node1 = nodes.Find(NN->node1);
t_index node2 = nodes.Find(NN->node2);
// Merge the nodes in the union-find data structure by making them
// children of a new node
// if the distance is appropriate
if (NN->dist < thr_cutoff)
{
parent = nodes.Union(node1, node2);
S[parent] = S[node1] + S[node2];
}
}
//Get cluster labels
int * T = new int[N];
for (t_index i = 0; i < N; i++)
{
T[i] = nodes.Find(i);
}
//Find largest cluster
int S_max = distance(S, max_element(S, S + 2*N-1));
//Find inliers, compute center of votes
points_inlier.reserve(S[S_max]);
classes_inlier.reserve(S[S_max]);
center.x = center.y = 0;
for (size_t i = 0; i < points.size(); i++)
{
//If point is in consensus cluster
if (T[i] == S_max)
{
points_inlier.push_back(points[i]);
classes_inlier.push_back(classes[i]);
center.x += votes[i].x;
center.y += votes[i].y;
}
}
center.x /= points_inlier.size();
center.y /= points_inlier.size();
delete[] D;
delete[] S;
delete[] T;
FILE_LOG(logDEBUG) << "Consensus::findConsensus() return";
}
} /* namespace cmt */