# Identification of Location and Camera Parameters for Public Live Streaming Web Cameras
## 5 Examples
### Example 2. More Radial Distortion and Vegetation, More Calibration Points
We are ready to compute the orientation matrix \(R\) (20)-(26), so we can convert \(F_{cnu}\) coordinates to \(F_{c}\) (27). We select the points to approximate the road surface (see Table 5). Figure 11: Cropped and interpolated part of image \(\dot{\Phi}\). Figure 10: The image \(\Phi\) after compensation of radial distortion; Example 2, image \(\dot{\Phi}=\Theta(\Phi)\) without postprocessing. We calculate road plane \(\Pi\) with (29) and (32):  
\[p=(0.00006008,2.93113699,130.65768737). \tag{52}\]  
We choose four corners of \(g_{1},g_{2},g_{3}\), and \(g_{4}\) of \(\hat{Q}_{im}\) in the image \(\hat{\Phi}\) (see Table 6 and Figure 12). Let us try the nonrectangular area \(\hat{Q}_{im}\). We calculate the lines that bound domain \(\hat{Q}_{im}\) with (41) and detect the set of pixel coordinates that belongs to \(\hat{Q}_{im}\). We compute the \(Q_{c}\) as \(\xi(\hat{Q}_{im})\) with (48) and (35)-(39). Next, we convert the pixel coordinates from \(Q_{c}\) to \(F_{\pi}\) with (43)-(47) and (49) and save the result. The distances in Q correspond to estimates obtained online and a simple rangefinder (accuracy up to a meter). We plan more accurate assessments using the geodetic tools. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Corner** & **Name** & \(\mathbf{u}\) & \(\mathbf{v}\) \\ \hline top left & \(g_{1}\) & \(509\) & \(962\) \\ bottom left & \(g_{2}\) & \(993\) & \(1078\) \\ top right & \(g_{3}\) & \(1630\) & \(498\) \\ bottom right & \(g_{4}\) & \(1858\) & \(558\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Domain \(\hat{Q}_{im}\) corners coordinates in \(\hat{\Phi}\), Example 2. Figure 12: The \(Q_{\pi}\) set visualization in plane \(\Pi\) for case (50). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Num** & **Lat** & **Long** & **Height** & \(\mathbf{x_{c}}\) & \(\mathbf{y_{c}}\) & \(\mathbf{z_{c}}\) \\ \hline
1 & \(43.168145^{\circ}\) & \(131.916262^{\circ}\) & \(13.5\) & \(0\) & \(0\) & \(-0.1\) \\
2 & \(43.168192^{\circ}\) & \(131.916673^{\circ}\) & \(13.5\) & \(33.82\) & \(5.44\) & \(-0.1\) \\
3 & \(43.168275^{\circ}\) & \(131.917036^{\circ}\) & \(14\) & \(63.34\) & \(14.67\) & \(-0.1\) \\
4 & \(43.168367^{\circ}\) & \(131.917515^{\circ}\) & \(14.3\) & \(102.29\) & \(24.89\) & \(-0\) \\
6 & \(43.168519^{\circ}\) & \(131.918425^{\circ}\) & \(15\) & \(176.29\) & \(41.77\) & \(0.1\) \\
7 & \(43.167925^{\circ}\) & \(131.916348^{\circ}\) & \(14\) & \(7.4\) & \(-24.22\) & \(-0.1\) \\
8 & \(43.168005^{\circ}\) & \(131.916540^{\circ}\) & \(14\) & \(23.01\) & \(-15.33\) & \(-0.1\) \\
9 & \(43.168011^{\circ}\) & \(131.916699^{\circ}\) & \(14\) & \(35.94\) & \(-14.66\) & \(-0.1\) \\
10 & \(43.168110^{\circ}\) & \(131.917060^{\circ}\) & \(14\) & \(65.3\) & \(-3.67\) & \(-0.1\) \\
11 & \(43.168210^{\circ}\) & \(131.917540^{\circ}\) & \(14.5\) & \(104.33\) & \(7.44\) & \(-0.1\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The points used to approximate road plane \(\Pi\) (global and \(F_{c}\) coordinates, \(F_{c}\) and altitudes given in meters). We repeat the needed steps for hypothesis (51) and compare the results (see Figures 12 and 13). We observed a change in the geometry of \(Q_{\pi}\) for the hypothesis (51). For example, the pedestrian crossing changed its inclination; the road began to expand to the right. In this example, it is not easy to obtain several long parallel lines due to vegetation, and it is an argument for examining the cameras in a suitable season.