/******************* TO DO *********************
* leastSquaresFit:
* INPUT:
* f1, f2: source feature sets
* matches: correspondences between f1 and f2
* m: motion model
* inliers: inlier match indices (indexes into 'matches' array)
* M: transformation matrix (output)
* OUTPUT:
* compute the transformation from f1 to f2 using only the inliers
* and return it in M
*/
int leastSquaresFit(const FeatureSet &f1, const FeatureSet &f2,
const vector<FeatureMatch> &matches, MotionModel m,
const vector<int> &inliers, CTransform3x3& M)
{
// This function needs to handle two possible motion models,
// This function needs to handle two possible motion models,
// pure translations and full homographies.
switch (m) {
case eTranslate: {
// for spherically warped images, the transformation is a
// for spherically warped images, the transformation is a
// translation and only has two degrees of freedom
//
// therefore, we simply compute the average translation vector
// between the feature in f1 and its match in f2 for all inliers
double u = 0;
double v = 0;
for (int i=0; i < (int) inliers.size(); i++) {
// BEGIN TODO
// use this loop to compute the average translation vector
// over all inliers
int m1 = matches.at(inliers.at(i)).id1;
int m2 = matches.at(inliers.at(i)).id2;
u += f1[m1].x - f2[m2].x;
v += f1[m1].y - f2[m2].y;
printf("TODO: %s:%d\n", __FILE__, __LINE__);
// END TODO
}
u /= inliers.size();
v /= inliers.size();
M = CTransform3x3::Translation((float) u, (float) v);
break;
}
case eHomography: {
M = CTransform3x3();
// BEGIN TODO
// Compute a homography M using all inliers.
// This should call ComputeHomography.
vector<FeatureMatch> inmatches;
for (int bo = 0; bo < inliers.size(); bo++)
{
FeatureMatch mat;
mat = matches.at(inliers.at(bo));
inmatches.push_back(mat);
}
M = ComputeHomography(f1, f2, inmatches);
break;
}
case eRotate3D: {
cout << "3D Rotation is not supported by this project";
break;
}
}
// END TODO
return 0;
}
// Compute MOPs descriptors.
void ComputeMOPSDescriptors(CFloatImage &image, FeatureSet &features)
{
CFloatImage grayImage=ConvertToGray(image);
CFloatImage blurredImage;
Convolve(grayImage, blurredImage, ConvolveKernel_7x7);
CFloatImage postHomography = CFloatImage();
CFloatImage gaussianImage = GetImageFromMatrix((float *)gaussian5x5Float, 5, 5);
//first make the image invariant to changes in illumination by subtracting off the mean
int grayHeight = grayImage.Shape().height;
int grayWidth = grayImage.Shape().width;
// now make this rotation invariant
vector<Feature>::iterator featureIterator = features.begin();
while (featureIterator != features.end()) {
Feature &f = *featureIterator;
CTransform3x3 scaleTransform = CTransform3x3();
CTransform3x3 translationNegative;
CTransform3x3 translationPositive;
CTransform3x3 rotation;
double scaleFactor = 41/8;
scaleTransform[0][0] = scaleFactor;
scaleTransform[1][1] = scaleFactor;
translationNegative = translationNegative.Translation(f.x,f.y);
translationPositive = translationPositive.Translation(-4, -4);
rotation = rotation.Rotation(f.angleRadians * 180/ PI);
CTransform3x3 finalTransformation = translationNegative * rotation * scaleTransform * translationPositive;
//CFloatImage sample61x61Window =
//CFloatImage pixelWindow = GetXWindowAroundPixel(grayImage, f.x, f.y, 61);
WarpGlobal(blurredImage, postHomography, finalTransformation, eWarpInterpLinear, 1.0f);
//now we get the 41x41 box around the feature
for(int row=0; row< 8; row++)
{
for(int col=0;col< 8;col++)
{
f.data.push_back(postHomography.Pixel(col, row, 0));
}
}
/*
// now we do the subsampling first round to reduce to a 20x20
int imgSize = 41;
subsample(&f, imgSize, gaussianImage);
//second round of subsampling to get it to a 10x10
imgSize = 20;
subsample(&f, imgSize, gaussianImage);
imgSize = 10;
CFloatImage img = featureToImage(f, imgSize, imgSize);
CFloatImage blurredImg(img.Shape());
Convolve(img, blurredImg, gaussianImage);
featuresFromImage(&f,blurredImg,imgSize,imgSize);
int count = 0;
for(int y=0; y<imgSize; y++)
{
for(int x=0; x<imgSize; x++)
{
if(x == 3 || x == 7 || y == 3 || y == 7)
{
f.data.erase(f.data.begin() + count);
}
else
{
count++;
}
}
}
*/
normalizeIntensities(&f, 8, 8);
featureIterator++;
}
}
/******************* TO DO 5 *********************
* BlendImages:
* INPUT:
* ipv: list of input images and their relative positions in the mosaic
* blendWidth: width of the blending function
* OUTPUT:
* create & return final mosaic by blending all images
* and correcting for any vertical drift
*/
CByteImage BlendImages(CImagePositionV& ipv, float blendWidth)
{
// Assume all the images are of the same shape (for now)
CByteImage& img0 = ipv[0].img;
CShape sh = img0.Shape();
int width = sh.width;
int height = sh.height;
int nBands = sh.nBands;
int dim[2] = {width, height};
// Compute the bounding box for the mosaic
int n = ipv.size();
float min_x = 0, min_y = 0;
float max_x = 0, max_y = 0;
int i;
float dy = 0;
for (i = 0; i < n; i++)
{
CTransform3x3 &pos = ipv[i].position;
CVector3 corners[4];//表示图片的4个角的坐标，分别为左下，右下，左上，右上
corners[0][0] = 0.0;
corners[0][1] = 0.0;
corners[0][2] = 1.0;
corners[1][0] = width - 1;
corners[1][1] = 0.0;
corners[1][2] = 1.0;
corners[2][0] = 0.0;
corners[2][1] = height - 1;
corners[2][2] = 1.0;
corners[3][0] = width - 1;
corners[3][1] = height - 1;
corners[3][2] = 1.0;
corners[0] = pos * corners[0];
corners[1] = pos * corners[1];
corners[2] = pos * corners[2];
corners[3] = pos * corners[3];
corners[0][0] /= corners[0][2];
corners[0][1] /= corners[0][2];
corners[1][0] /= corners[0][2];
corners[1][1] /= corners[0][2];
corners[2][0] /= corners[0][2];
corners[2][1] /= corners[0][2];
corners[3][0] /= corners[0][2];
corners[3][1] /= corners[0][2];
// *** BEGIN TODO #1 ***
// add some code here to update min_x, ..., max_y
//Use c0 and c3 to get the range of x and y.
int iminx, iminy, imaxx, imaxy;
ImageBoundingBox(img0, pos, iminx, iminy, imaxx, imaxy);
if (i == 0)
{
dy += imaxy;
}
if (i == n - 1)
{
dy -= imaxy;
}
/*if (min_x > corners[0][0])
{
min_x = corners[0][0];
}
if (max_x < corners[3][0])
{
max_x = corners[3][0];
}
if (min_y > corners[0][1])
{
min_y = corners[0][1];
}
if (max_y < corners[3][1])
{
max_y = corners[3][1];
}
*/
min_x = min(min_x, float(iminx));
min_y = min(min_y, float(iminy));
max_x = max(max_x, float(imaxx));
max_y = max(max_y, float(imaxy));
// *** END TODO #1 ***
}
// Create a floating point accumulation image
CShape mShape((int)(ceil(max_x) - floor(min_x)),
(int)(ceil(max_y) - floor(min_y)), nBands);
CFloatImage accumulator(mShape);
accumulator.ClearPixels();
double x_init, x_final;
double y_init, y_final;
// Add in all of the images
for (i = 0; i < n; i++) {
CTransform3x3 &M = ipv[i].position;
CTransform3x3 M_t = CTransform3x3::Translation(-min_x, -min_y) * M;
CByteImage& img = ipv[i].img;
// Perform the accumulation
AccumulateBlend(img, accumulator, M_t, blendWidth);
if (i == 0) {
CVector3 p;
p[0] = 0.5 * width;
p[1] = 0.0;
p[2] = 1.0;
p = M_t * p;
x_init = p[0];
y_init = p[1];
} else if (i == n - 1) {
CVector3 p;
p[0] = 0.5 * width;
p[1] = 0.0;
p[2] = 1.0;
p = M_t * p;
x_final = p[0];
y_final = p[1];
}
}
// Normalize the results
CByteImage compImage(mShape);
NormalizeBlend(accumulator, compImage);
bool debug_comp = false;
if (debug_comp)
WriteFile(compImage, "tmp_comp.tga");
// Allocate the final image shape
CShape cShape(mShape.width - width, height, nBands);
CByteImage croppedImage(cShape);
// Compute the affine deformation
CTransform3x3 A = CTransform3x3();
// *** BEGIN TODO #2 ***
// fill in the right entries in A to trim the left edge and
// to take out the vertical drift
A[0][2] = width /2;
A[1][0] = dy / (mShape.width - width);
// *** END TODO #2 ***
// Warp and crop the composite
WarpGlobal(compImage, croppedImage, A, eWarpInterpLinear);
// WarpGlobal(compImage, croppedImage, A, eWarpInterpNearest); //similar as linear
// WarpGlobal(compImage, croppedImage, A, eWarpInterpCubic); //all pixels are black
return croppedImage;
}
/******************* TO DO 5 *********************
* BlendImages:
* INPUT:
* ipv: list of input images and their relative positions in the mosaic
* blendWidth: width of the blending function
* OUTPUT:
* create & return final mosaic by blending all images
* and correcting for any vertical drift
*/
CByteImage BlendImages(CImagePositionV& ipv, float blendWidth)
{
// Assume all the images are of the same shape (for now)
CByteImage& img0 = ipv[0].img;
CShape sh = img0.Shape();
int width = sh.width;
int height = sh.height;
int nBands = sh.nBands;
// int dim[2] = {width, height};
int n = ipv.size();
if (n == 0) return CByteImage(0,0,1);
bool is360 = false;
// Hack to detect if this is a 360 panorama
if (ipv[0].imgName == ipv[n-1].imgName)
is360 = true;
// Compute the bounding box for the mosaic
float min_x = FLT_MAX, min_y = FLT_MAX;
float max_x = 0, max_y = 0;
int i;
for (i = 0; i < n; i++)
{
CTransform3x3 &T = ipv[i].position;
// BEGIN TODO
// add some code here to update min_x, ..., max_y
printf("TODO: %s:%d\n", __FILE__, __LINE__);
// END TODO
}
// Create a floating point accumulation image
CShape mShape((int)(ceil(max_x) - floor(min_x)),
(int)(ceil(max_y) - floor(min_y)), nBands + 1);
CFloatImage accumulator(mShape);
accumulator.ClearPixels();
double x_init, x_final;
double y_init, y_final;
// Add in all of the images
for (i = 0; i < n; i++) {
// Compute the sub-image involved
CTransform3x3 &M = ipv[i].position;
CTransform3x3 M_t = CTransform3x3::Translation(-min_x, -min_y) * M;
CByteImage& img = ipv[i].img;
// Perform the accumulation
AccumulateBlend(img, accumulator, M_t, blendWidth);
if (i == 0) {
CVector3 p;
p[0] = 0.5 * width;
p[1] = 0.0;
p[2] = 1.0;
p = M_t * p;
x_init = p[0];
y_init = p[1];
} else if (i == n - 1) {
CVector3 p;
p[0] = 0.5 * width;
p[1] = 0.0;
p[2] = 1.0;
p = M_t * p;
x_final = p[0];
y_final = p[1];
}
}
// Normalize the results
mShape = CShape((int)(ceil(max_x) - floor(min_x)),
(int)(ceil(max_y) - floor(min_y)), nBands);
CByteImage compImage(mShape);
NormalizeBlend(accumulator, compImage);
bool debug_comp = false;
if (debug_comp)
WriteFile(compImage, "tmp_comp.tga");
// Allocate the final image shape
int outputWidth = 0;
if (is360) {
outputWidth = mShape.width - width;
} else {
outputWidth = mShape.width;
}
CShape cShape(outputWidth, mShape.height, nBands);
CByteImage croppedImage(cShape);
// Compute the affine transformation
CTransform3x3 A = CTransform3x3(); // identify transform to initialize
// BEGIN TODO
// fill in appropriate entries in A to trim the left edge and
// to take out the vertical drift if this is a 360 panorama
// (i.e. is360 is true)
printf("TODO: %s:%d\n", __FILE__, __LINE__);
// END TODO
// Warp and crop the composite
WarpGlobal(compImage, croppedImage, A, eWarpInterpLinear);
return croppedImage;
}
