Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

677 lines
22 KiB

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <map>
#include <ctype.h>
#include <stdio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
static bool readCameraMatrix(const string& filename,
Mat& cameraMatrix, Mat& distCoeffs,
Size& calibratedImageSize )
{
FileStorage fs(filename, FileStorage::READ);
fs["image_width"] >> calibratedImageSize.width;
fs["image_height"] >> calibratedImageSize.height;
fs["distortion_coefficients"] >> distCoeffs;
fs["camera_matrix"] >> cameraMatrix;
if( distCoeffs.type() != CV_64F )
distCoeffs = Mat_<double>(distCoeffs);
if( cameraMatrix.type() != CV_64F )
cameraMatrix = Mat_<double>(cameraMatrix);
return true;
}
static bool readModelViews( const string& filename, vector<Point3f>& box,
vector<string>& imagelist,
vector<Rect>& roiList, vector<Vec6f>& poseList )
{
imagelist.resize(0);
roiList.resize(0);
poseList.resize(0);
box.resize(0);
FileStorage fs(filename, FileStorage::READ);
if( !fs.isOpened() )
return false;
fs["box"] >> box;
FileNode all = fs["views"];
if( all.type() != FileNode::SEQ )
return false;
FileNodeIterator it = all.begin(), it_end = all.end();
for(; it != it_end; ++it)
{
FileNode n = *it;
imagelist.push_back((string)n["image"]);
FileNode nr = n["roi"];
roiList.push_back(Rect((int)nr[0], (int)nr[1], (int)nr[2], (int)nr[3]));
FileNode np = n["pose"];
poseList.push_back(Vec6f((float)np[0], (float)np[1], (float)np[2],
(float)np[3], (float)np[4], (float)np[5]));
}
return true;
}
struct PointModel
{
vector<Point3f> points;
vector<vector<int> > didx;
Mat descriptors;
string name;
};
static void writeModel(const string& modelFileName, const string& modelname,
const PointModel& model)
{
FileStorage fs(modelFileName, FileStorage::WRITE);
fs << modelname << "{" <<
"points" << "[:" << model.points << "]" <<
"idx" << "[:";
for( size_t i = 0; i < model.didx.size(); i++ )
fs << "[:" << model.didx[i] << "]";
fs << "]" << "descriptors" << model.descriptors;
}
static void unpackPose(const Vec6f& pose, Mat& R, Mat& t)
{
Mat rvec = (Mat_<double>(3,1) << pose[0], pose[1], pose[2]);
t = (Mat_<double>(3,1) << pose[3], pose[4], pose[5]);
Rodrigues(rvec, R);
}
static Mat getFundamentalMat( const Mat& R1, const Mat& t1,
const Mat& R2, const Mat& t2,
const Mat& cameraMatrix )
{
Mat_<double> R = R2*R1.t(), t = t2 - R*t1;
double tx = t.at<double>(0,0), ty = t.at<double>(1,0), tz = t.at<double>(2,0);
Mat E = (Mat_<double>(3,3) << 0, -tz, ty, tz, 0, -tx, -ty, tx, 0)*R;
Mat iK = cameraMatrix.inv();
Mat F = iK.t()*E*iK;
#if 0
static bool checked = false;
if(!checked)
{
vector<Point3f> objpoints(100);
Mat O(objpoints);
randu(O, Scalar::all(-10), Scalar::all(10));
vector<Point2f> imgpoints1, imgpoints2;
projectPoints(Mat(objpoints), R1, t1, cameraMatrix, Mat(), imgpoints1);
projectPoints(Mat(objpoints), R2, t2, cameraMatrix, Mat(), imgpoints2);
double* f = (double*)F.data;
for( size_t i = 0; i < objpoints.size(); i++ )
{
Point2f p1 = imgpoints1[i], p2 = imgpoints2[i];
double diff = p2.x*(f[0]*p1.x + f[1]*p1.y + f[2]) +
p2.y*(f[3]*p1.x + f[4]*p1.y + f[5]) +
f[6]*p1.x + f[7]*p1.y + f[8];
CV_Assert(fabs(diff) < 1e-3);
}
checked = true;
}
#endif
return F;
}
static void findConstrainedCorrespondences(const Mat& _F,
const vector<KeyPoint>& keypoints1,
const vector<KeyPoint>& keypoints2,
const Mat& descriptors1,
const Mat& descriptors2,
vector<Vec2i>& matches,
double eps, double ratio)
{
float F[9]={0};
int dsize = descriptors1.cols;
Mat Fhdr = Mat(3, 3, CV_32F, F);
_F.convertTo(Fhdr, CV_32F);
matches.clear();
for( size_t i = 0; i < keypoints1.size(); i++ )
{
Point2f p1 = keypoints1[i].pt;
double bestDist1 = DBL_MAX, bestDist2 = DBL_MAX;
int bestIdx1 = -1, bestIdx2 = -1;
const float* d1 = descriptors1.ptr<float>(i);
for( size_t j = 0; j < keypoints2.size(); j++ )
{
Point2f p2 = keypoints2[j].pt;
double e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) +
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) +
F[6]*p1.x + F[7]*p1.y + F[8];
if( fabs(e) > eps )
continue;
const float* d2 = descriptors2.ptr<float>(j);
double dist = 0;
int k = 0;
for( ; k <= dsize - 8; k += 8 )
{
float t0 = d1[k] - d2[k], t1 = d1[k+1] - d2[k+1];
float t2 = d1[k+2] - d2[k+2], t3 = d1[k+3] - d2[k+3];
float t4 = d1[k+4] - d2[k+4], t5 = d1[k+5] - d2[k+5];
float t6 = d1[k+6] - d2[k+6], t7 = d1[k+7] - d2[k+7];
dist += t0*t0 + t1*t1 + t2*t2 + t3*t3 +
t4*t4 + t5*t5 + t6*t6 + t7*t7;
if( dist >= bestDist2 )
break;
}
if( dist < bestDist2 )
{
for( ; k < dsize; k++ )
{
float t = d1[k] - d2[k];
dist += t*t;
}
if( dist < bestDist1 )
{
bestDist2 = bestDist1;
bestIdx2 = bestIdx1;
bestDist1 = dist;
bestIdx1 = (int)j;
}
else if( dist < bestDist2 )
{
bestDist2 = dist;
bestIdx2 = (int)j;
}
}
}
if( bestIdx1 >= 0 && bestDist1 < bestDist2*ratio )
{
Point2f p2 = keypoints1[bestIdx1].pt;
double e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) +
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) +
F[6]*p1.x + F[7]*p1.y + F[8];
if( e > eps*0.25 )
continue;
double threshold = bestDist1/ratio;
const float* d22 = descriptors2.ptr<float>(bestIdx1);
size_t i1 = 0;
for( ; i1 < keypoints1.size(); i1++ )
{
if( i1 == i )
continue;
Point2f p1 = keypoints1[i1].pt;
const float* d11 = descriptors1.ptr<float>(i1);
double dist = 0;
e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) +
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) +
F[6]*p1.x + F[7]*p1.y + F[8];
if( fabs(e) > eps )
continue;
for( int k = 0; k < dsize; k++ )
{
float t = d11[k] - d22[k];
dist += t*t;
if( dist >= threshold )
break;
}
if( dist < threshold )
break;
}
if( i1 == keypoints1.size() )
matches.push_back(Vec2i(i,bestIdx1));
}
}
}
static Point3f findRayIntersection(Point3f k1, Point3f b1, Point3f k2, Point3f b2)
{
float a[4], b[2], x[2];
a[0] = k1.dot(k1);
a[1] = a[2] = -k1.dot(k2);
a[3] = k2.dot(k2);
b[0] = k1.dot(b2 - b1);
b[1] = k2.dot(b1 - b2);
Mat_<float> A(2, 2, a), B(2, 1, b), X(2, 1, x);
solve(A, B, X);
float s1 = X.at<float>(0, 0);
float s2 = X.at<float>(1, 0);
return (k1*s1 + b1 + k2*s2 + b2)*0.5f;
}
static Point3f triangulatePoint(const vector<Point2f>& ps,
const vector<Mat>& Rs,
const vector<Mat>& ts,
const Mat& cameraMatrix)
{
Mat_<double> K(cameraMatrix);
15 years ago
/*if( ps.size() > 2 )
{
Mat_<double> L(ps.size()*3, 4), U, evalues;
Mat_<double> P(3,4), Rt(3,4), Rt_part1=Rt.colRange(0,3), Rt_part2=Rt.colRange(3,4);
for( size_t i = 0; i < ps.size(); i++ )
{
double x = ps[i].x, y = ps[i].y;
Rs[i].convertTo(Rt_part1, Rt_part1.type());
ts[i].convertTo(Rt_part2, Rt_part2.type());
P = K*Rt;
for( int k = 0; k < 4; k++ )
{
L(i*3, k) = x*P(2,k) - P(0,k);
L(i*3+1, k) = y*P(2,k) - P(1,k);
L(i*3+2, k) = x*P(1,k) - y*P(0,k);
}
}
eigen(L.t()*L, evalues, U);
CV_Assert(evalues(0,0) >= evalues(3,0));
double W = fabs(U(3,3)) > FLT_EPSILON ? 1./U(3,3) : 0;
return Point3f((float)(U(3,0)*W), (float)(U(3,1)*W), (float)(U(3,2)*W));
}
15 years ago
else*/
{
Mat_<float> iK = K.inv();
Mat_<float> R1t = Mat_<float>(Rs[0]).t();
Mat_<float> R2t = Mat_<float>(Rs[1]).t();
Mat_<float> m1 = (Mat_<float>(3,1) << ps[0].x, ps[0].y, 1);
Mat_<float> m2 = (Mat_<float>(3,1) << ps[1].x, ps[1].y, 1);
Mat_<float> K1 = R1t*(iK*m1), K2 = R2t*(iK*m2);
Mat_<float> B1 = -R1t*Mat_<float>(ts[0]);
Mat_<float> B2 = -R2t*Mat_<float>(ts[1]);
return findRayIntersection(*K1.ptr<Point3f>(), *B1.ptr<Point3f>(),
*K2.ptr<Point3f>(), *B2.ptr<Point3f>());
}
}
void triangulatePoint_test(void)
{
int i, n = 100;
vector<Point3f> objpt(n), delta1(n), delta2(n);
Mat rvec1(3,1,CV_32F), tvec1(3,1,CV_64F);
Mat rvec2(3,1,CV_32F), tvec2(3,1,CV_64F);
Mat objptmat(objpt), deltamat1(delta1), deltamat2(delta2);
randu(rvec1, Scalar::all(-10), Scalar::all(10));
randu(tvec1, Scalar::all(-10), Scalar::all(10));
randu(rvec2, Scalar::all(-10), Scalar::all(10));
randu(tvec2, Scalar::all(-10), Scalar::all(10));
randu(objptmat, Scalar::all(-10), Scalar::all(10));
double eps = 1e-2;
randu(deltamat1, Scalar::all(-eps), Scalar::all(eps));
randu(deltamat2, Scalar::all(-eps), Scalar::all(eps));
vector<Point2f> imgpt1, imgpt2;
Mat_<float> cameraMatrix(3,3);
double fx = 1000., fy = 1010., cx = 400.5, cy = 300.5;
cameraMatrix << fx, 0, cx, 0, fy, cy, 0, 0, 1;
projectPoints(Mat(objpt)+Mat(delta1), rvec1, tvec1, cameraMatrix, Mat(), imgpt1);
projectPoints(Mat(objpt)+Mat(delta2), rvec2, tvec2, cameraMatrix, Mat(), imgpt2);
vector<Point3f> objptt(n);
vector<Point2f> pts(2);
vector<Mat> Rv(2), tv(2);
Rodrigues(rvec1, Rv[0]);
Rodrigues(rvec2, Rv[1]);
tv[0] = tvec1; tv[1] = tvec2;
for( i = 0; i < n; i++ )
{
pts[0] = imgpt1[i]; pts[1] = imgpt2[i];
objptt[i] = triangulatePoint(pts, Rv, tv, cameraMatrix);
}
double err = norm(Mat(objpt), Mat(objptt), CV_C);
CV_Assert(err < 1e-1);
}
typedef pair<int, int> Pair2i;
typedef map<Pair2i, int> Set2i;
struct EqKeypoints
{
EqKeypoints(const vector<int>* _dstart, const Set2i* _pairs)
: dstart(_dstart), pairs(_pairs) {}
bool operator()(const Pair2i& a, const Pair2i& b) const
{
return pairs->find(Pair2i(dstart->at(a.first) + a.second,
dstart->at(b.first) + b.second)) != pairs->end();
}
const vector<int>* dstart;
const Set2i* pairs;
};
static void build3dmodel( const Ptr<FeatureDetector>& detector,
const Ptr<DescriptorExtractor>& descriptorExtractor,
const vector<Point3f>& modelBox,
const vector<string>& imageList,
const vector<Rect>& roiList,
const vector<Vec6f>& poseList,
const Mat& cameraMatrix,
PointModel& model )
{
int progressBarSize = 10;
const double Feps = 5;
const double DescriptorRatio = 0.7;
vector<vector<KeyPoint> > allkeypoints;
vector<int> dstart;
vector<float> alldescriptorsVec;
vector<Vec2i> pairwiseMatches;
vector<Mat> Rs, ts;
int descriptorSize = 0;
Mat descriptorbuf;
Set2i pairs, keypointsIdxMap;
model.points.clear();
model.didx.clear();
dstart.push_back(0);
size_t nimages = imageList.size();
size_t nimagePairs = (nimages - 1)*nimages/2 - nimages;
printf("\nComputing descriptors ");
// 1. find all the keypoints and all the descriptors
for( size_t i = 0; i < nimages; i++ )
{
Mat img = imread(imageList[i], 1), gray;
cvtColor(img, gray, CV_BGR2GRAY);
vector<KeyPoint> keypoints;
detector->detect(gray, keypoints);
descriptorExtractor->compute(gray, keypoints, descriptorbuf);
Point2f roiofs = roiList[i].tl();
for( size_t k = 0; k < keypoints.size(); k++ )
keypoints[k].pt += roiofs;
allkeypoints.push_back(keypoints);
Mat buf = descriptorbuf;
if( !buf.isContinuous() || buf.type() != CV_32F )
{
buf.release();
descriptorbuf.convertTo(buf, CV_32F);
}
descriptorSize = buf.cols;
size_t prev = alldescriptorsVec.size();
size_t delta = buf.rows*buf.cols;
alldescriptorsVec.resize(prev + delta);
std::copy(buf.ptr<float>(), buf.ptr<float>() + delta,
alldescriptorsVec.begin() + prev);
dstart.push_back(dstart.back() + keypoints.size());
Mat R, t;
unpackPose(poseList[i], R, t);
Rs.push_back(R);
ts.push_back(t);
if( (i+1)*progressBarSize/nimages > i*progressBarSize/nimages )
{
putchar('.');
fflush(stdout);
}
}
Mat alldescriptors(alldescriptorsVec.size()/descriptorSize, descriptorSize, CV_32F,
&alldescriptorsVec[0]);
printf("\nOk. total images = %d. total keypoints = %d\n",
(int)nimages, alldescriptors.rows);
printf("\nFinding correspondences ");
int pairsFound = 0;
vector<Point2f> pts_k(2);
vector<Mat> Rs_k(2), ts_k(2);
//namedWindow("img1", 1);
//namedWindow("img2", 1);
// 2. find pairwise correspondences
for( size_t i = 0; i < nimages; i++ )
for( size_t j = i+1; j < nimages; j++ )
{
const vector<KeyPoint>& keypoints1 = allkeypoints[i];
const vector<KeyPoint>& keypoints2 = allkeypoints[j];
Mat descriptors1 = alldescriptors.rowRange(dstart[i], dstart[i+1]);
Mat descriptors2 = alldescriptors.rowRange(dstart[j], dstart[j+1]);
Mat F = getFundamentalMat(Rs[i], ts[i], Rs[j], ts[j], cameraMatrix);
findConstrainedCorrespondences( F, keypoints1, keypoints2,
descriptors1, descriptors2,
pairwiseMatches, Feps, DescriptorRatio );
//pairsFound += (int)pairwiseMatches.size();
//Mat img1 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1);
//Mat img2 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)j), 1);
//double avg_err = 0;
for( size_t k = 0; k < pairwiseMatches.size(); k++ )
{
int i1 = pairwiseMatches[k][0], i2 = pairwiseMatches[k][1];
pts_k[0] = keypoints1[i1].pt;
pts_k[1] = keypoints2[i2].pt;
Rs_k[0] = Rs[i]; Rs_k[1] = Rs[j];
ts_k[0] = ts[i]; ts_k[1] = ts[j];
Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix);
vector<Point3f> objpts;
objpts.push_back(objpt);
vector<Point2f> imgpts1, imgpts2;
projectPoints(Mat(objpts), Rs_k[0], ts_k[0], cameraMatrix, Mat(), imgpts1);
projectPoints(Mat(objpts), Rs_k[1], ts_k[1], cameraMatrix, Mat(), imgpts2);
double e1 = norm(imgpts1[0] - keypoints1[i1].pt);
double e2 = norm(imgpts2[0] - keypoints2[i2].pt);
15 years ago
if( e1 + e2 > 5 )
continue;
pairsFound++;
//model.points.push_back(objpt);
pairs[Pair2i(i1+dstart[i], i2+dstart[j])] = 1;
pairs[Pair2i(i2+dstart[j], i1+dstart[i])] = 1;
keypointsIdxMap[Pair2i(i,i1)] = 1;
keypointsIdxMap[Pair2i(j,i2)] = 1;
//CV_Assert(e1 < 5 && e2 < 5);
//Scalar color(rand()%256,rand()%256, rand()%256);
//circle(img1, keypoints1[i1].pt, 2, color, -1, CV_AA);
//circle(img2, keypoints2[i2].pt, 2, color, -1, CV_AA);
}
//printf("avg err = %g\n", pairwiseMatches.size() ? avg_err/(2*pairwiseMatches.size()) : 0.);
//imshow("img1", img1);
//imshow("img2", img2);
//waitKey();
if( (i+1)*progressBarSize/nimagePairs > i*progressBarSize/nimagePairs )
{
putchar('.');
fflush(stdout);
}
}
printf("\nOk. Total pairs = %d\n", pairsFound );
// 3. build the keypoint clusters
vector<Pair2i> keypointsIdx;
Set2i::iterator kpidx_it = keypointsIdxMap.begin(), kpidx_end = keypointsIdxMap.end();
for( ; kpidx_it != kpidx_end; ++kpidx_it )
keypointsIdx.push_back(kpidx_it->first);
printf("\nClustering correspondences ");
vector<int> labels;
int nclasses = partition( keypointsIdx, labels, EqKeypoints(&dstart, &pairs) );
printf("\nOk. Total classes (i.e. 3d points) = %d\n", nclasses );
model.descriptors.create(keypointsIdx.size(), descriptorSize, CV_32F);
model.didx.resize(nclasses);
model.points.resize(nclasses);
vector<vector<Pair2i> > clusters(nclasses);
for( size_t i = 0; i < keypointsIdx.size(); i++ )
clusters[labels[i]].push_back(keypointsIdx[i]);
// 4. now compute 3D points corresponding to each cluster and fill in the model data
printf("\nComputing 3D coordinates ");
int globalDIdx = 0;
for( int k = 0; k < nclasses; k++ )
{
int i, n = (int)clusters[k].size();
pts_k.resize(n);
Rs_k.resize(n);
ts_k.resize(n);
model.didx[k].resize(n);
for( i = 0; i < n; i++ )
{
int imgidx = clusters[k][i].first, ptidx = clusters[k][i].second;
Mat dstrow = model.descriptors.row(globalDIdx);
alldescriptors.row(dstart[imgidx] + ptidx).copyTo(dstrow);
model.didx[k][i] = globalDIdx++;
pts_k[i] = allkeypoints[imgidx][ptidx].pt;
Rs_k[i] = Rs[imgidx];
ts_k[i] = ts[imgidx];
}
Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix);
model.points[k] = objpt;
if( (i+1)*progressBarSize/nclasses > i*progressBarSize/nclasses )
{
putchar('.');
fflush(stdout);
}
}
Mat img(768, 1024, CV_8UC3);
vector<Point2f> imagePoints;
namedWindow("Test", 1);
// visualize the cloud
for( size_t i = 0; i < nimages; i++ )
{
img = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1);
projectPoints(Mat(model.points), Rs[i], ts[i], cameraMatrix, Mat(), imagePoints);
for( int k = 0; k < (int)imagePoints.size(); k++ )
circle(img, imagePoints[k], 2, Scalar(0,255,0), -1, CV_AA, 0);
imshow("Test", img);
int c = waitKey();
if( c == 'q' || c == 'Q' )
break;
}
}
int main(int argc, char** argv)
{
triangulatePoint_test();
const char* help = "Usage: build3dmodel -i <intrinsics_filename>\n"
"\t[-d <detector>] [-de <descriptor_extractor>] -m <model_name>\n";
if(argc < 3)
{
puts(help);
return 0;
}
const char* intrinsicsFilename = 0;
const char* modelName = 0;
const char* detectorName = "SURF";
const char* descriptorExtractorName = "SURF";
vector<Point3f> modelBox;
vector<string> imageList;
vector<Rect> roiList;
vector<Vec6f> poseList;
for( int i = 1; i < argc; i++ )
{
if( strcmp(argv[i], "-i") == 0 )
intrinsicsFilename = argv[++i];
else if( strcmp(argv[i], "-m") == 0 )
modelName = argv[++i];
else if( strcmp(argv[i], "-d") == 0 )
detectorName = argv[++i];
else if( strcmp(argv[i], "-de") == 0 )
descriptorExtractorName = argv[++i];
else
{
printf("Incorrect option\n");
puts(help);
return 0;
}
}
if( !intrinsicsFilename || !modelName )
{
printf("Some of the required parameters are missing\n");
puts(help);
return 0;
}
Mat cameraMatrix, distCoeffs;
Size calibratedImageSize;
readCameraMatrix(intrinsicsFilename, cameraMatrix, distCoeffs, calibratedImageSize);
Ptr<FeatureDetector> detector = createDetector(detectorName);
Ptr<DescriptorExtractor> descriptorExtractor = createDescriptorExtractor(descriptorExtractorName);
string modelIndexFilename = format("%s_segm/frame_index.yml", modelName);
if(!readModelViews( modelIndexFilename, modelBox, imageList, roiList, poseList))
{
printf("Can not read the model. Check the parameters and the working directory\n");
puts(help);
return 0;
}
PointModel model;
model.name = modelName;
build3dmodel( detector, descriptorExtractor, modelBox,
imageList, roiList, poseList, cameraMatrix, model );
string outputModelName = format("%s_model.yml.gz", modelName);
printf("\nDone! Now saving the model ...\n");
writeModel(outputModelName, modelName, model);
return 0;
}