雙目相機標定以及立體測距原理及OpenCV實現
阿新 • • 發佈：2017-07-01
ada eps 左右 flag 並且 length turn iostream 中一
左右相機校正效果：
單目相機標定的目標是獲取相機的內參和外參，內參（1/dx,1/dy,Cx,Cy,f）表征了相機的內部結構參數，外參是相機的旋轉矩陣R和平移向量t。內參中dx和dy是相機單個感光單元芯片的長度和寬度，是一個物理尺寸，有時候會有dx=dy，這時候感光單元是一個正方形。Cx和Cy分別代表相機感光芯片的中心點在x和y方向上可能存在的偏移，因為芯片在安裝到相機模組上的時候，由於制造精度和組裝工藝的影響，很難做到中心完全重合。f代表相機的焦距。
雙目標定的第一步需要分別獲取左右相機的內外參數，之後通過立體標定對左右兩幅圖像進行立體校準和對其，最後就是確定兩個相機的相對位置關系，即中心距。
首先看一下雙目測距的基本原理：
假設有一個點p，沿著垂直於相機中心連線方向上下移動，則其在左右相機上的成像點的位置會不斷變化，即d=x1-x2的大小不斷變化，並且點p和相機之間的距離Z跟視差d存在著反比關系。上式中視差d可以通過兩個相機中心距T減去p點分別在左右圖像上的投影點偏離中心點的值獲得，所以只要獲取到了兩個相機的中心距T,就可以評估出p點距離相機的距離，這個中心距T也是雙目標定中需要確立的參數之一。
當然這一切有一個前提就是要在兩個相機成像上定位到同一個點p上，就是要把左右兩個圖片的點匹配起來，這就涉及到雙目校正的動作。如果通過一幅圖片上一個點的特征在另一個二維圖像空間上匹配對應點，這個過程會非常耗時。為了減少匹配搜索的運算量，我們可以利用極限約束使得對應點的匹配由二維搜索空間降到一維搜索空間。
這時候要用雙目校正把消除畸變後的兩幅圖像在水平方向嚴格的對齊，使得兩幅圖像的對極線恰好在同一水平線上，這樣一幅圖像上任意一點與其在另一幅圖像上的匹配點就必然具有相同的行號，只需要在該行進行一維搜索就可匹配到對應點。
下邊Opencv雙目相機校正的代碼是在自帶的程序stereo_calib.cpp基礎上修改的，位置在“XX\opencv\sources\samples\cpp\”，使用時拷貝目錄下的26張圖片和stereo_calib.xml到當前工程目錄下，並在工程調試->命令參數裏設置參數為：StereoCalibration -w 9 -h 6 stereo_calib.xml
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <vector>
#include <string>
#include <algorithm>
#include <iostream>
#include <iterator>
#include <stdio.h>
#include <stdlib.h>
#include <ctype.h>
using namespace cv;
using namespace std;
static void StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=true, bool showRectified=true)
{
if( imagelist.size() % 2 != 0 )
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return;
}
bool displayCorners = true;//true;
const int maxScale = 2;
const float squareSize = 1.f; // Set this to your actual square size
// ARRAY AND VECTOR STORAGE:
vector<vector<Point2f> > imagePoints[2];
vector<vector<Point3f> > objectPoints;
Size imageSize;
int i, j, k, nimages = (int)imagelist.size()/2;
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
vector<string> goodImageList;
for( i = j = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
const string& filename = imagelist[i*2+k];
Mat img = imread(filename, 0);
if(img.empty())
break;
if( imageSize == Size() )
imageSize = img.size();
else if( img.size() != imageSize )
{
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
break;
}
bool found = false;
vector<Point2f>& corners = imagePoints[k][j];
for( int scale = 1; scale <= maxScale; scale++ )
{
Mat timg;
if( scale == 1 )
timg = img;
else
resize(img, timg, Size(), scale, scale);
found = findChessboardCorners(timg, boardSize, corners,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE);
if( found )
{
if( scale > 1 )
{
Mat cornersMat(corners);
cornersMat *= 1./scale;
}
break;
}
}
if( displayCorners )
{
cout << filename << endl;
Mat cimg, cimg1;
cvtColor(img, cimg, COLOR_GRAY2BGR);
drawChessboardCorners(cimg, boardSize, corners, found);
double sf = 640./MAX(img.rows, img.cols);
resize(cimg, cimg1, Size(), sf, sf);
imshow("corners", cimg1);
char c = (char)waitKey(500);
if( c == 27 || c == ‘q‘ || c == ‘Q‘ ) //Allow ESC to quit
exit(-1);
}
else
putchar(‘.‘);
if( !found )
break;
cornerSubPix(img, corners, Size(11,11), Size(-1,-1),
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,
30, 0.01));
}
if( k == 2 )
{
goodImageList.push_back(imagelist[i*2]);
goodImageList.push_back(imagelist[i*2+1]);
j++;
}
}
cout << j << " pairs have been successfully detected.\n";
nimages = j;
if( nimages < 2 )
{
cout << "Error: too little pairs to run the calibration\n";
return;
}
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
objectPoints.resize(nimages);
for( i = 0; i < nimages; i++ )
{
for( j = 0; j < boardSize.height; j++ )
for( k = 0; k < boardSize.width; k++ )
objectPoints[i].push_back(Point3f(k*squareSize, j*squareSize, 0));
}
cout << "Running stereo calibration ...\n";
Mat cameraMatrix[2], distCoeffs[2];
cameraMatrix[0] = Mat::eye(3, 3, CV_64F);
cameraMatrix[1] = Mat::eye(3, 3, CV_64F);
Mat R, T, E, F;
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_RATIONAL_MODEL +
CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5);
cout << "done with RMS error=" << rms << endl;
// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
double err = 0;
int npoints = 0;
vector<Vec3f> lines[2];
for( i = 0; i < nimages; i++ )
{
int npt = (int)imagePoints[0][i].size();
Mat imgpt[2];
for( k = 0; k < 2; k++ )
{
imgpt[k] = Mat(imagePoints[k][i]);
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
}
for( j = 0; j < npt; j++ )
{
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
cout << "average reprojection err = " << err/npoints << endl;
// save intrinsic parameters
FileStorage fs("intrinsics.yml", CV_STORAGE_WRITE);
if( fs.isOpened() )
{
fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
"M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
fs.release();
}
else
cout << "Error: can not save the intrinsic parameters\n";
Mat R1, R2, P1, P2, Q;
Rect validRoi[2];
stereoRectify(cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, R1, R2, P1, P2, Q,
CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);
fs.open("extrinsics.yml", CV_STORAGE_WRITE);
if( fs.isOpened() )
{
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
fs.release();
}
else
cout << "Error: can not save the extrinsic parameters\n";
// OpenCV can handle left-right
// or up-down camera arrangements
bool isVerticalStereo = fabs(P2.at<double>(1, 3)) > fabs(P2.at<double>(0, 3));
// COMPUTE AND DISPLAY RECTIFICATION
if( !showRectified )
return;
Mat rmap[2][2];
// IF BY CALIBRATED (BOUGUET‘S METHOD)
if( useCalibrated )
{
// we already computed everything
}
// OR ELSE HARTLEY‘S METHOD
else
// use intrinsic parameters of each camera, but
// compute the rectification transformation directly
// from the fundamental matrix
{
vector<Point2f> allimgpt[2];
for( k = 0; k < 2; k++ )
{
for( i = 0; i < nimages; i++ )
std::copy(imagePoints[k][i].begin(), imagePoints[k][i].end(), back_inserter(allimgpt[k]));
}
F = findFundamentalMat(Mat(allimgpt[0]), Mat(allimgpt[1]), FM_8POINT, 0, 0);
Mat H1, H2;
stereoRectifyUncalibrated(Mat(allimgpt[0]), Mat(allimgpt[1]), F, imageSize, H1, H2, 3);
R1 = cameraMatrix[0].inv()*H1*cameraMatrix[0];
R2 = cameraMatrix[1].inv()*H2*cameraMatrix[1];
P1 = cameraMatrix[0];
P2 = cameraMatrix[1];
}
//Precompute maps for cv::remap()
initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1, imageSize, CV_16SC2, rmap[0][0], rmap[0][1]);
initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2, imageSize, CV_16SC2, rmap[1][0], rmap[1][1]);
Mat canvas;
double sf;
int w, h;
if( !isVerticalStereo )
{
sf = 600./MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h, w*2, CV_8UC3);
}
else
{
sf = 300./MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h*2, w, CV_8UC3);
}
for( i = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
Mat img = imread(goodImageList[i*2+k], 0), rimg, cimg;
remap(img, rimg, rmap[k][0], rmap[k][1], CV_INTER_LINEAR);
imshow("單目相機校正",rimg);
waitKey();
cvtColor(rimg, cimg, COLOR_GRAY2BGR);
Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
resize(cimg, canvasPart, canvasPart.size(), 0, 0, CV_INTER_AREA);
if( useCalibrated )
{
Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),
cvRound(validRoi[k].width*sf), cvRound(validRoi[k].height*sf));
rectangle(canvasPart, vroi, Scalar(0,0,255), 3, 8);
}
}
if( !isVerticalStereo )
for( j = 0; j < canvas.rows; j += 16 )
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
else
for( j = 0; j < canvas.cols; j += 16 )
line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
imshow("雙目相機校正對齊", canvas);
waitKey();
char c = (char)waitKey();
if( c == 27 || c == ‘q‘ || c == ‘Q‘ )
break;
}
}
static bool readStringList( const string& filename, vector<string>& l )
{
l.resize(0);
FileStorage fs(filename, FileStorage::READ);
if( !fs.isOpened() )
return false;
FileNode n = fs.getFirstTopLevelNode();
if( n.type() != FileNode::SEQ )
return false;
FileNodeIterator it = n.begin(), it_end = n.end();
for( ; it != it_end; ++it )
l.push_back((string)*it);
return true;
}
int main(int argc, char** argv)
{
Size boardSize;
string imagelistfn;
bool showRectified = true;
for( int i = 1; i < argc; i++ )
{
if( string(argv[i]) == "-w" )
{
if( sscanf(argv[++i], "%d", &boardSize.width) != 1 || boardSize.width <= 0 )
{
cout << "invalid board width" << endl;
return -1;
}
}
else if( string(argv[i]) == "-h" )
{
if( sscanf(argv[++i], "%d", &boardSize.height) != 1 || boardSize.height <= 0 )
{
cout << "invalid board height" << endl;
return -1;
}
}
else if( string(argv[i]) == "-nr" )
showRectified = false;
else if( string(argv[i]) == "--help" )
return -1;
else if( argv[i][0] == ‘-‘ )
{
cout << "invalid option " << argv[i] << endl;
return 0;
}
else
imagelistfn = argv[i];
}
if( imagelistfn == "" )
{
imagelistfn = "stereo_calib.xml";
boardSize = Size(9, 6);
}
else if( boardSize.width <= 0 || boardSize.height <= 0 )
{
cout << "if you specified XML file with chessboards, you should also specify the board width and height (-w and -h options)" << endl;
return 0;
}
vector<string> imagelist;
bool ok = readStringList(imagelistfn, imagelist);
if(!ok || imagelist.empty())
{
cout << "can not open " << imagelistfn << " or the string list is empty" << endl;
return -1;
}
StereoCalib(imagelist, boardSize, true, showRectified);
return 0;
}
右相機其中一個標定圖片查找到的角點：
左相機其中一個標定圖片查找到的角點：
右相機單目校正：
左相機單目校正：
左右相機雙目立體校正：
雙目相機標定後，可以看到左右相機對應匹配點基本上已經水平對齊。
之後在該程序基礎上運行stereo_match.cpp，求左右相機的視差。同樣工程調試->命令參數裏設置參數為：left01.jpg right01.jpg --algorithm=bm -i intrinsics.yml -e extrinsics.yml：
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/contrib/contrib.hpp"
#include <stdio.h>
using namespace cv;
static void saveXYZ(const char* filename, const Mat& mat)
{
const double max_z = 1.0e4;
FILE* fp = fopen(filename, "wt");
for(int y = 0; y < mat.rows; y++)
{
for(int x = 0; x < mat.cols; x++)
{
Vec3f point = mat.at<Vec3f>(y, x);
if(fabs(point[2] - max_z) < FLT_EPSILON || fabs(point[2]) > max_z) continue;
fprintf(fp, "%f %f %f\n", point[0], point[1], point[2]);
}
}
fclose(fp);
}
int main(int argc, char** argv)
{
const char* algorithm_opt = "--algorithm=";
const char* maxdisp_opt = "--max-disparity=";
const char* blocksize_opt = "--blocksize=";
const char* nodisplay_opt = "--no-display";
const char* scale_opt = "--scale=";
if(argc < 3)
{
return 0;
}
const char* img1_filename = 0;
const char* img2_filename = 0;
const char* intrinsic_filename = 0;
const char* extrinsic_filename = 0;
const char* disparity_filename = 0;
const char* point_cloud_filename = 0;
enum { STEREO_BM=0, STEREO_SGBM=1, STEREO_HH=2, STEREO_VAR=3 };
int alg = STEREO_SGBM;
int SADWindowSize = 0, numberOfDisparities = 0;
bool no_display = false;
float scale = 1.f;
StereoBM bm;
StereoSGBM sgbm;
StereoVar var;
for( int i = 1; i < argc; i++ )
{
if( argv[i][0] != ‘-‘ )
{
if( !img1_filename )
img1_filename = argv[i];
else
img2_filename = argv[i];
}
else if( strncmp(argv[i], algorithm_opt, strlen(algorithm_opt)) == 0 )
{
char* _alg = argv[i] + strlen(algorithm_opt);
alg = strcmp(_alg, "bm") == 0 ? STEREO_BM :
strcmp(_alg, "sgbm") == 0 ? STEREO_SGBM :
strcmp(_alg, "hh") == 0 ? STEREO_HH :
strcmp(_alg, "var") == 0 ? STEREO_VAR : -1;
if( alg < 0 )
{
printf("Command-line parameter error: Unknown stereo algorithm\n\n");
return -1;
}
}
else if( strncmp(argv[i], maxdisp_opt, strlen(maxdisp_opt)) == 0 )
{
if( sscanf( argv[i] + strlen(maxdisp_opt), "%d", &numberOfDisparities ) != 1 ||
numberOfDisparities < 1 || numberOfDisparities % 16 != 0 )
{
printf("Command-line parameter error: The max disparity (--maxdisparity=<...>) must be a positive integer divisible by 16\n");
return -1;
}
}
else if( strncmp(argv[i], blocksize_opt, strlen(blocksize_opt)) == 0 )
{
if( sscanf( argv[i] + strlen(blocksize_opt), "%d", &SADWindowSize ) != 1 ||
SADWindowSize < 1 || SADWindowSize % 2 != 1 )
{
printf("Command-line parameter error: The block size (--blocksize=<...>) must be a positive odd number\n");
return -1;
}
}
else if( strncmp(argv[i], scale_opt, strlen(scale_opt)) == 0 )
{
if( sscanf( argv[i] + strlen(scale_opt), "%f", &scale ) != 1 || scale < 0 )
{
printf("Command-line parameter error: The scale factor (--scale=<...>) must be a positive floating-point number\n");
return -1;
}
}
else if( strcmp(argv[i], nodisplay_opt) == 0 )
no_display = true;
else if( strcmp(argv[i], "-i" ) == 0 )
intrinsic_filename = argv[++i];
else if( strcmp(argv[i], "-e" ) == 0 )
extrinsic_filename = argv[++i];
else if( strcmp(argv[i], "-o" ) == 0 )
disparity_filename = argv[++i];
else if( strcmp(argv[i], "-p" ) == 0 )
point_cloud_filename = argv[++i];
else
{
printf("Command-line parameter error: unknown option %s\n", argv[i]);
return -1;
}
}
if( !img1_filename || !img2_filename )
{
printf("Command-line parameter error: both left and right images must be specified\n");
return -1;
}
if( (intrinsic_filename != 0) ^ (extrinsic_filename != 0) )
{
printf("Command-line parameter error: either both intrinsic and extrinsic parameters must be specified, or none of them (when the stereo pair is already rectified)\n");
return -1;
}
if( extrinsic_filename == 0 && point_cloud_filename )
{
printf("Command-line parameter error: extrinsic and intrinsic parameters must be specified to compute the point cloud\n");
return -1;
}
int color_mode = alg == STEREO_BM ? 0 : -1;
Mat img1 = imread(img1_filename, color_mode);
Mat img2 = imread(img2_filename, color_mode);
if (img1.empty())
{
printf("Command-line parameter error: could not load the first input image file\n");
return -1;
}
if (img2.empty())
{
printf("Command-line parameter error: could not load the second input image file\n");
return -1;
}
if (scale != 1.f)
{
Mat temp1, temp2;
int method = scale < 1 ? INTER_AREA : INTER_CUBIC;
resize(img1, temp1, Size(), scale, scale, method);
img1 = temp1;
resize(img2, temp2, Size(), scale, scale, method);
img2 = temp2;
}
Size img_size = img1.size();
Rect roi1, roi2;
Mat Q;
if( intrinsic_filename )
{
// reading intrinsic parameters
FileStorage fs(intrinsic_filename, CV_STORAGE_READ);
if(!fs.isOpened())
{
printf("Failed to open file %s\n", intrinsic_filename);
return -1;
}
Mat M1, D1, M2, D2;
fs["M1"] >> M1;
fs["D1"] >> D1;
fs["M2"] >> M2;
fs["D2"] >> D2;
M1 *= scale;
M2 *= scale;
fs.open(extrinsic_filename, CV_STORAGE_READ);
if(!fs.isOpened())
{
printf("Failed to open file %s\n", extrinsic_filename);
return -1;
}
Mat R, T, R1, P1, R2, P2;
fs["R"] >> R;
fs["T"] >> T;
stereoRectify( M1, D1, M2, D2, img_size, R, T, R1, R2, P1, P2, Q, CALIB_ZERO_DISPARITY, -1, img_size, &roi1, &roi2 );
Mat map11, map12, map21, map22;
initUndistortRectifyMap(M1, D1, R1, P1, img_size, CV_16SC2, map11, map12);
initUndistortRectifyMap(M2, D2, R2, P2, img_size, CV_16SC2, map21, map22);
Mat img1r, img2r;
remap(img1, img1r, map11, map12, INTER_LINEAR);
remap(img2, img2r, map21, map22, INTER_LINEAR);
img1 = img1r;
img2 = img2r;
}
numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : ((img_size.width/8) + 15) & -16;
bm.state->roi1 = roi1;
bm.state->roi2 = roi2;
bm.state->preFilterCap = 31;
bm.state->SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 9;
bm.state->minDisparity = 0;
bm.state->numberOfDisparities = numberOfDisparities;
bm.state->textureThreshold = 10;
bm.state->uniquenessRatio = 15;
bm.state->speckleWindowSize = 100;
bm.state->speckleRange = 32;
bm.state->disp12MaxDiff = 1;
sgbm.preFilterCap = 63;
sgbm.SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 3;
int cn = img1.channels();
sgbm.P1 = 8*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
sgbm.P2 = 32*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
sgbm.minDisparity = 0;
sgbm.numberOfDisparities = numberOfDisparities;
sgbm.uniquenessRatio = 10;
sgbm.speckleWindowSize = bm.state->speckleWindowSize;
sgbm.speckleRange = bm.state->speckleRange;
sgbm.disp12MaxDiff = 1;
sgbm.fullDP = alg == STEREO_HH;
var.levels = 3; // ignored with USE_AUTO_PARAMS
var.pyrScale = 0.5; // ignored with USE_AUTO_PARAMS
var.nIt = 25;
var.minDisp = -numberOfDisparities;
var.maxDisp = 0;
var.poly_n = 3;
var.poly_sigma = 0.0;
var.fi = 15.0f;
var.lambda = 0.03f;
var.penalization = var.PENALIZATION_TICHONOV; // ignored with USE_AUTO_PARAMS
var.cycle = var.CYCLE_V; // ignored with USE_AUTO_PARAMS
var.flags = var.USE_SMART_ID | var.USE_AUTO_PARAMS | var.USE_INITIAL_DISPARITY | var.USE_MEDIAN_FILTERING ;
Mat disp, disp8;
//Mat img1p, img2p, dispp;
//copyMakeBorder(img1, img1p, 0, 0, numberOfDisparities, 0, IPL_BORDER_REPLICATE);
//copyMakeBorder(img2, img2p, 0, 0, numberOfDisparities, 0, IPL_BORDER_REPLICATE);
int64 t = getTickCount();
if( alg == STEREO_BM )
bm(img1, img2, disp);
else if( alg == STEREO_VAR ) {
var(img1, img2, disp);
}
else if( alg == STEREO_SGBM || alg == STEREO_HH )
sgbm(img1, img2, disp);
t = getTickCount() - t;
printf("Time elapsed: %fms\n", t*1000/getTickFrequency());
//disp = dispp.colRange(numberOfDisparities, img1p.cols);
waitKey();
if( alg != STEREO_VAR )
disp.convertTo(disp8, CV_8U, 255/(numberOfDisparities*16.));
else
disp.convertTo(disp8, CV_8U);
if( !no_display )
{
namedWindow("左相機", 0);
imshow("左相機", img1);
namedWindow("右相機", 0);
imshow("右相機", img2);
imshow("左右相機視差圖", disp8);
printf("press any key to continue...");
fflush(stdout);
waitKey();
printf("\n");
}
if(disparity_filename)
imwrite(disparity_filename, disp8);
if(point_cloud_filename)
{
printf("storing the point cloud...");
fflush(stdout);
Mat xyz;
reprojectImageTo3D(disp, xyz, Q, true);
saveXYZ(point_cloud_filename, xyz);
printf("\n");
}
return 0;
}
左右相機校正效果：
左右相機視差圖：
視差用亮度表示，越亮表示當前位置距離相機越遠。
雙目相機標定以及立體測距原理及OpenCV實現