The method of calculating the focal length f from the matching points of the two images.

The method of calculating the focal length f from the matching points of the two images.

Find two focal length calculation methods from the network
1. The focal length of the two images based on the matrix H (taken from the opencv code of panorama Mosaic)

// Calculate the focal length f from the homography matrix H of the two images. Void focalsFromHomography (const Mat & H, double & f0, double & f1, bool & f0_ OK, bool & f1_ OK) {CV_Assert (H. type () = CV_64F & H. size () = Size (3, 3); const double * h = H. ptr
 
  
(); // H is a vector of double d1, d2; // denominator of double v1, v2; // candidate f1_ OK = true for focal length squared values; d1 = h [6] * h [7]; d2 = (h [7]-h [6]) * (h [7] + h [6]); v1 =-(h [0] * h [1] + h [3] * h [4])/d1; v2 = (h [0] * h [0] + h [3] * h [3]-h [1] * h [1]-h [4] * h [4]) /d2; if (v1 <v2) std: swap (v1, v2); if (v1> 0 & v2> 0) f1 = std: sqrt (std :: abs (d1)> std: abs (d2 )? V1: v2); else if (v1> 0) f1 = std: sqrt (v1); else fse OK = false; f0_ OK = true; d1 = h [0] * h [3] + h [1] * h [4]; d2 = h [0] * h [0] + h [1] * h [1]-h [3] * h [3]-h [4] * h [4 ]; v1 =-h [2] * h [5]/d1; v2 = (h [5] * h [5]-h [2] * h [2]) /d2; if (v1 <v2) std: swap (v1, v2); if (v1> 0 & v2> 0) f0 = std: sqrt (std :: abs (d1)> std: abs (d2 )? V1: v2); else if (v1> 0) f0 = std: sqrt (v1); else f0_ OK = false ;}
 

Use the following test

// Read two graphs Mat img1 = imread (name1); // Mat img2 = imread (name2); // match the vector
 
  
Kp1, kp2; vector
  
   
Matches; meMatch2 (img1, img2, kp1, kp2, matches); // generates a matching point vector
   
    
Points1, points2; get_match_points (kp1, kp2, matches, points1, points2); // four pairs of image points correspond to HomographyMat H = findHomography (points1, points2, 0); double f0; double f1; bool f0_ OK; bool f1_ OK; // calculate the focal length f from the homography matrix H of the two images. FocalsFromHomography (H, f0, f1, f0_ OK, f1_ OK); if (f0_ OK) std: cout <"Figure 1 focal length:" <f0 <'\ n '; if (f1_ OK) std: cout <"Figure 2 focal length:" <f1 <'\ n ';
   
  
 

Result:

Figure 1 focal length: 81.9963
Figure 2 focal length: 992.465
Only Figure 2 is accurate.

-= ----------------- Separation line -------------------------- =-=

2. Focal Length of matching points in two graphs f (from a pole calibration toolkit matlab)

Function [f] = compIntrinsic (ml, mr, width, height) % calculates a focal length % ml. mr is the corresponding point % width in the image, height is the size of the image (used to obtain the focal length and image Center) % options = optimset ('babal', 'off'); a0 = [0 0 0 0, 0]; [af, resnorm, residual, exitflag, output, lambda, Jacob Bian] = lsqnonlin (@ (x) costRectif (x, width, height, ml, mr), a0 ,... [-pi/2,-pi/2,-pi/2,-pi/2,-pi/2,-1.5], [pi/2, pi/2, pi/2, pi/2, pi/2, 1.5], options); counter = 0; while af (6)> 1 | af (6) <-1 counter = counter + 1; disp ('focus out of range; retry (random )... '); a0 = [0 0 0 0 0, 2 * rand-1.0]; [af, resnorm] = lsqnonlin (@ (x) costRectif (x, width, height, ml, mr), a0 ,... [-pi/2,-pi/2,-pi/2,-pi/2,-pi/2,-1.5], [pi/2, pi/2, pi/2, pi/2, pi/2, 1.5], options); if counter> 20 warning ('the focal point in the range is not found ') break endendf = 3 ^ af (6) * (width + height); % disp (['focal length: f = 'num2str (f)]);

Test

F = compIntrinsic (ml, mr, width, height); % ml, mr a matching point of 2xn matrix. width, height is the image length, width disp (['focal length: f = 'num2str (f)]);

Result
Focal Length: f = 892.7031
Basic accuracy.