// Initialize global alignment of all images.
int initGlobalAlign(const vector<FeatureSet> &fs, int minMatches, MotionModel m, float f, int width, int height, int nRANSAC, double RANSACthresh, AlignMatrix &am, vector<CTransform3x3> &ms) {
int n = fs.size();
CTransform3x3 transMat;
vector<FeatureMatch> matches;
// create the n-by-n alignment matrix
am.resize(n);
for (int i=0; i<n; i++)
am[i].resize(n);
for (int i=0; i<n; i++) {
for (int j=0; j<n; j++) {
if (i != j) {
printf("matching image %d with image %d, ", i, j);
// BEGIN TODO
// write code to fill in the information for am[i][j]
//
// you'll need to call your feature matching routine,
// then your pair alignment routine
matches.clear();
int count = 0;
FeatureSet f1 = fs[i];
int m = f1.size();
FeatureSet f2 = fs[j];
int n = f2.size();
double d;
double dBest[2];
int idBest;
FeatureMatch feamatch;
for (int i = 0; i < m; i++)
{
dBest[0] = 1e64;
dBest[1] = 1e64 + 1;
idBest = 0;
for (int j = 0; j < n; j++)
{
d = Euclidean(f1[i], f2[j]);
if (d < dBest[0]) {
dBest[1] = dBest[0];
dBest[0] = d;
idBest = f2[j].id;
}
else if (d < dBest[1])
{
dBest[1] = d;
}
}
if (sqrt(dBest[0] / dBest[1]) < 1.0)
{
feamatch.id = idBest;
matches.push_back(feamatch);
count++;
}
else
{
feamatch.id = -1;
matches.push_back(feamatch);
}
}
if (count < minMatches)
{
am[i][j].matches = matches;
am[i][j].inliers.clear();
am[i][j].r = transMat;
}
else
{
am[i][j].matches = matches;
alignImagePair(fs[i], fs[j], matches, eRotate3D, f, width, height, nRANSAC, RANSACthresh, transMat, am[i][j].inliers);
am[i][j].r = transMat;
}
// END TODO
printf("%d inliers\n", am[i][j].inliers.size());
if ((int) am[i][j].inliers.size() < minMatches)
am[i][j].inliers.clear();
}
}
}
vector<AlignmentImage> nodes(n);
for (int i=1; i<n; i++) {
nodes[i].added = false;
nodes[i].nBest = 0;
nodes[i].imageID = i;
nodes[i].parentID = -1;
}
// create the image heap
ImageHeap heap(nodes);
// add the first image and update the match quality of
// its neighbors
nodes[0].added = true;
for (int j=1; j<n; j++) {
int nMatches = am[0][j].inliers.size();
if (nodes[j].nBest < nMatches) {
heap.increaseKey(nodes[j].heapIndex, nMatches);
nodes[j].parentID = 0;
}
}
AlignmentImage *nextImage;
// add the rest of the images
for (int i=0; i<n-1; i++) {
nextImage = heap.extractMax();
if (nextImage->nBest == 0) {
// image set seems to be disconnected
return -1;
}
nextImage->added = true;
int id = nextImage->imageID;
int pid = nextImage->parentID;
// compute the global alignment of the extracted image
nextImage->r = am[pid][id].r * nodes[pid].r;
// update the match quality for its neighbor images
for (int j=0; j<n; j++) {
if ((id != j) && (!nodes[j].added)) {
int nMatches = am[id][j].inliers.size();
if (nodes[j].nBest < nMatches) {
heap.increaseKey(nodes[j].heapIndex, nMatches);
nodes[j].parentID = id;
}
}
}
}
ms.clear();
// put the global transformations into the output array
for (int i=0; i<n; i++) {
ms.push_back(nodes[i].r);
}
return 0;
}
// Initialize global alignment of all images.
int initGlobalAlign(const vector<FeatureSet> &fs, int minMatches, MotionModel m, float f, const vector< pair<int,int> >& WH, int nRANSAC, double RANSACthresh, AlignMatrix &am, vector<CTransform3x3> &ms) {
int n = fs.size();
// create the n-by-n alignment matrix
am.resize(n);
for (int i=0; i<n; i++)
am[i].resize(n);
vector<FeatureMatch> matches;
CTransform3x3 transMat;
for (int i=0; i<n; i++) {
for (int j=0; j<n; j++) {
if (i != j) {
printf("matching image %d with image %d, ", i, j);
// BEGIN TODO
// write code to fill in the information for am[i][j]
//
// you'll need to call your feature matching routine,
// then your pair alignment routine
matches.clear();
int count = MatchFeaturesByDistRatio(fs[i], fs[j],matches);
if(count < minMatches)
{
am[i][j].matches = matches;
am[i][j].inliers.clear();
am[i][j].r = transMat;
}
else
{
am[i][j].matches = matches;
if(ApproximateRotation)
am[i][j].inliers = alignPair(fs[i],fs[j],matches,eRotate3D,f,WH[i],WH[j],nRANSAC,RANSACthresh,transMat);
else
am[i][j].inliers = MyalignPair(fs[i],fs[j],matches,eRotate3D,f,WH[i],WH[j],nRANSAC,RANSACthresh,transMat);
am[i][j].r = transMat;
}
// END TODO
printf("%d inliers\n", am[i][j].inliers.size());
if ((int) am[i][j].inliers.size() < minMatches)
am[i][j].inliers.clear();
}
}
}
vector<AlignmentImage> nodes(n);
for (int i=1; i<n; i++) {
nodes[i].added = false;
nodes[i].nBest = 0;
nodes[i].imageID = i;
nodes[i].parentID = -1;
}
// create the image heap
ImageHeap heap(nodes);
// add the first image and update the match quality of
// its neighbors
nodes[0].added = true;
for (int j=1; j<n; j++) {
int nMatches = am[0][j].inliers.size();
if (nodes[j].nBest < nMatches) {
heap.increaseKey(nodes[j].heapIndex, nMatches);
nodes[j].parentID = 0;
}
}
AlignmentImage *nextImage;
// add the rest of the images
for (int i=0; i<n-1; i++) {
nextImage = heap.extractMax();
if (nextImage->nBest == 0) {
// image set seems to be disconnected
return -1;
}
nextImage->added = true;
int id = nextImage->imageID;
int pid = nextImage->parentID;
// compute the global alignment of the extracted image
nextImage->r = am[pid][id].r * nodes[pid].r;
// update the match quality for its neighbor images
for (int j=0; j<n; j++) {
if ((id != j) && (!nodes[j].added)) {
int nMatches = am[id][j].inliers.size();
if (nodes[j].nBest < nMatches) {
heap.increaseKey(nodes[j].heapIndex, nMatches);
nodes[j].parentID = id;
}
}
}
}
ms.clear();
// put the global transformations into the output array
for (int i=0; i<n; i++) {
ms.push_back(nodes[i].r);
}
return 0;
}
