mc2-scripts-and-benchmarks.git - Benchmarks and execution scripts for testing spatial isolation and SMT interference in MC^2

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Diffstat (limited to 'all_pairs/source/fmref/fmref.c')

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%init_intrinsic_param % %Initialization of the intrinsic parameters. %Runs as a script. % %INPUT: x_1,x_2,x_3,...: Feature locations on the images % X_1,X_2,X_3,...: Corresponding grid coordinates % %OUTPUT: fc: Camera focal length % cc: Principal point coordinates % kc: Distortion coefficients % KK: The camera matrix (containing fc and cc) % %Method: Computes the planar homographies H_1, H_2, H_3, ... and computes % the focal length fc from orthogonal vanishing points constraint. % The principal point cc is assumed at the center of the image. % Assumes no image distortion (kc = [0;0;0;0]) % %Note: The row vector active_images consists of zeros and ones. To deactivate an image, set the % corresponding entry in the active_images vector to zero. % % %Important function called within that program: % %compute_homography.m: Computes the planar homography between points on the grid in 3D, and the image plane. % % %VERY IMPORTANT: This function works onyl with 2D rigs. %In the future, a more general function will be there (working with 3D rigs as well). check_active_images; if ~exist(['x_' num2str(ind_active(1)) ]), click_calib; end; fprintf(1,'\nInitialization of the intrinsic parameters - Number of images: %d\n',length(ind_active)); % Initialize the homographies: for kk = 1:n_ima, eval(['x_kk = x_' num2str(kk) ';']); eval(['X_kk = X_' num2str(kk) ';']); if (isnan(x_kk(1,1))), if active_images(kk), fprintf(1,'WARNING: Cannot calibrate with image %d. Need to extract grid corners first.\n',kk) fprintf(1,' Set active_images(%d)=1; and run Extract grid corners.\n',kk) end; active_images(kk) = 0; end; if active_images(kk), eval(['H_' num2str(kk) ' = compute_homography(x_kk,X_kk(1:2,:));']); else eval(['H_' num2str(kk) ' = NaN*ones(3,3);']); end; end; check_active_images; % initial guess for principal point and distortion: if ~exist('nx'), [ny,nx] = size(I); end; c_init = [nx;ny]/2 - 0.5; % initialize at the center of the image k_init = [0;0;0;0]; % initialize to zero (no distortion) % Compute explicitely the focal length using all the (mutually orthogonal) vanishing points % note: The vanihing points are hidden in the planar collineations H_kk A = []; b = []; % matrix that subtract the principal point: Sub_cc = [1 0 -c_init(1);0 1 -c_init(2);0 0 1]; for kk=1:n_ima, if active_images(kk), eval(['Hkk = H_' num2str(kk) ';']); Hkk = Sub_cc * Hkk; % Extract vanishing points (direct and diagonals): V_hori_pix = Hkk(:,1); V_vert_pix = Hkk(:,2); V_diag1_pix = (Hkk(:,1)+Hkk(:,2))/2; V_diag2_pix = (Hkk(:,1)-Hkk(:,2))/2; V_hori_pix = V_hori_pix/norm(V_hori_pix); V_vert_pix = V_vert_pix/norm(V_vert_pix); V_diag1_pix = V_diag1_pix/norm(V_diag1_pix); V_diag2_pix = V_diag2_pix/norm(V_diag2_pix); a1 = V_hori_pix(1); b1 = V_hori_pix(2); c1 = V_hori_pix(3); a2 = V_vert_pix(1); b2 = V_vert_pix(2); c2 = V_vert_pix(3); a3 = V_diag1_pix(1); b3 = V_diag1_pix(2); c3 = V_diag1_pix(3); a4 = V_diag2_pix(1); b4 = V_diag2_pix(2); c4 = V_diag2_pix(3); A_kk = [a1*a2 b1*b2; a3*a4 b3*b4]; b_kk = -[c1*c2;c3*c4]; A = [A;A_kk]; b = [b;b_kk]; end; end; % use all the vanishing points to estimate focal length: f_init = sqrt(abs(1./(inv(A'*A)*A'*b))); % if using a two-focal model for initial guess %f_init = sqrt(b'*(sum(A')') / (b'*b)) * ones(2,1); % if single focal length model is used % Global calibration matrix (initial guess): KK = [f_init(1) 0 c_init(1);0 f_init(2) c_init(2); 0 0 1]; inv_KK = inv(KK); cc = c_init; fc = f_init; kc = k_init; fprintf(1,'\n\nCalibration parameters after initialization:\n\n'); fprintf(1,'Focal Length: fc = [ %3.5f %3.5f]\n',fc); fprintf(1,'Principal point: cc = [ %3.5f %3.5f]\n',cc); fprintf(1,'Distortion: kc = [ %3.5f %3.5f %3.5f %3.5f]\n\n',kc);


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