### Table 1. Intrinsic parameters calculated for our camera

"... In PAGE 5: ... To calculate these intrinsic and extrin- sic parameters, we have taken an image of a calibration frame, similarly to the approach presented by Ahn et al[1]. The intrinsic parameters we found are illus- trated in Table1 . The intrinsic parameters like Kappa,Cx, and Cy are used to calculate the degree of distortion for each pixel.... ..."

### Table 1: Calibration Using OpenCV cvCalibrateCamera() function with points ex- tracted automatically using the ARTag pattern array (mounted on the meddite panel) with two methods; using the marker center as a correspondence point, or using all four corners (2nd last and last column show respectively show error). Calibration pa- rameters are shown for the center method, only error is shown for the corner method.

2005

"... In PAGE 11: ...1. Table1 shows results using the meddite panel. Fig.... In PAGE 12: ...0 webcam (640x480), and a Logitech Quickcam Pro 4000 (640x480). Table1 shows the results of automatic calibration of these cameras using the... In PAGE 13: ... The intrinsic parameters are shown for the marker center approach and eval- uated by calculating statistics on the reprojection error, the standard deviation and maximum reprojection error are shown. Also shown (last column of Table1 ) are the reprojection error statistics using the marker corner method. 2.... In PAGE 18: ... The downside is of course that it could only calibrate 2/5 of the cameras. When comparing the results of Tables 4 and 5 to Table1 we see our ARTag-based method produces superior accuracy. 3.... ..."

### Table 2. Intrinsic camera calibration results for torso model. Intrinsic camera matrix Distortion coefficients

"... In PAGE 2: ... The chessboard plane contained 7x9 squares, so there where 48 inner corners, each square measuring 30x30mm. On Table2 and Table 3 are the intrinsic results for the torso and hand model, respectively. Regarding extrinsic calibration results, the stan- dard deviation of the reprojection error (in pixel), in both x and y directions, was [0.... ..."

### Table 4: Intrinsic camera parameters.

"... In PAGE 4: ... We set-up 8 control points at the object space, see table 1, and project them to the image space using the perspective camera model with specified extrinsic camera parameters presented in table 3. Table4 shows the intrinsic camera parameters, used in connection with the extrinsic parameters, to project the control point into the image space, see table 2. This example represents a typical aerial photography in photogrammetry.... ..."

Cited by 1

### Table 1: Results of the fundamental matrix estimation in the left camera. The cameras intrinsic parameters are then computed from the fundamental matrices. We show table 2 the intrinsic parameters obtained by the standard calibration method using each of the three images, and the results of our method, with the polynomial method, and the iterative method used to compute all the parameters, or just the scale factors, starting from the previous value. It can be noted that no initial guess is required at all for the general method. The scale factors are determined with a good accuracy, however, this is not the case for the coordinates of the principal point. Thus the best is to assume that it is at the center of the image. We have then compared in the table 3 the camera motion obtained directly from the projection matrices given by the classic calibration procedure, and the estimation by performing the decomposition of the fundamental matrices already obtained, and using the camera parameters obtained by the self-calibraion method. As the table shows the relative error on the rotation anglem and the angular error on the rotation axis and translation direction, it is easy to see that the estimation is accurate.

1993

### Table 4: The sensitivity of image-only batch estimation to camera intrinsics calibration errors and to image observation errors. The correct motion can be recovered from image measurements only given synthetic, zero noise observations and the intrinsics used to generate them (row 1). Estimating the motion from the synthetic image observations and a perturbed version of the camera intrinsics that generates the observations results in errors (rows 2-6) are much less than the errors that result from estimating the motion from the unperturbed camera intrinsics and noisy image observations (rows 7-11).

"... In PAGE 22: ... The estimated camera intrinsics, along with the reported standard deviations, are given in Table 3. The results are shown in rows 2-6 of Table4 . The resulting errors in the estimates are on the order of, or less, than the errors that we observe in the batch image-and-inertial estimates from the real image mea- surements.... In PAGE 22: ...0 pixels in each direction, which is the same ob- servation error distribution we have assumed in our experiments. The resulting errors are shown in rows 7-11 of Table4 , and are an order of magnitude larger... ..."

### Table 1: Results of the self-calibration: Intrinsic parameters Left camera Right camera distance

1996

"... In PAGE 15: ... However, a few points, especially those on the background are not well localized. We show in Table1 a subset of results of the self-calibration on this sequence of images, where... ..."

Cited by 32

### Table 1: Intrinsic camera parameters recovered by the calibration from known translations (the third row) are compared to the parameters obtained by zooming (the rst row) and by Tsai apos;s camera calibration method (the second row).

1998

"... In PAGE 5: ... Matrices K and R were then recovered by QR decomposition of A. Table1 shows camera intrinsic parameters K = 0 @ sx sk u0 sy v0 1 1 A (10) recovered by di erent methods. The principal point given by the proposed calibration from known trans- lations is much closer to the principal point measured by zooming than to the principal point obtained from Tsai apos;s calibration method [10].... ..."

### Table 1: A summary of some of the best work done on camera calibration from unknown scenes. The (*) indicates our contribution.

1998

"... In PAGE 1: ... Since that time various methods have been developed to deal with different situations. Table1 summarises the major contributors to date. In this paper we address one of the few cases which has not yet been explored, that of a stationary camera which may rotate and change its intrinsics.... ..."

Cited by 36

### Table 1: A summary of some of the best work done on camera calibration from unknown scenes. The (*) indicates our contribution.

1998

"... In PAGE 1: ... Since that time various methods have been developed to deal with different situations. Table1 summarises the major contributors to date. In this paper we address one of the few cases which has not yet been explored, that of a stationary camera which may rotate and change its intrinsics.... ..."

Cited by 36