# A Framework for the Detection of Search and Rescue Patterns Using Shapelet Classification
## 4 Experimental Evaluation & Results
### Classification on Real Data
In Table 5, we report on the number of trajectory chunks in which a SAR maneuver has been detected, using only the bearing (left part) and using both bearing and bearing change features (right part) as input. We report the numbers for the 5 cargo vessels that we processed. The table contains pairs of rows referring to the right (clockwise) and left (anti-clockwise) movement of the vessel during the maneuver. In the plots that we provide, this difference is not obvious but is clearly depicted in the bearing and bearing change patterns. Figure 6: An example of a real trajectory and its pre-processing, using the Scaled down, RDP and trajectory segmentation techniques. The first message conveyed from the results is that the Spiral movement pattern was never detected in the trajectories of these vessels. Furthermore, the Sector and Steps patterns are the most frequently detected in the dataset. A careful examination of the detected cases reveals several false positives, which is mainly due to the simplicity of the Steps maneuver. The result of this simplicity is that even when a vessel is performing a random maneuver that contains a step at some point, the classifier matches the respective shapelets and recognizes a Steps pattern. On the contrary, in the case of the Sector and Spiral movements, the SAR pattern is too complex and probably in the real case hard to perform perfectly. A last but most important fact is that when bearing change is used together with bearing, the ensemble of shapelets allows to capture more features of the pattern and reduce the number of detected cases, thus reducing recall but increasing the precision of the pattern detection task. Finally, it is interesting to show some patterns that have been detected by our classifiers and comprise SAR maneuvers. The plots of Figure 7 show chunks (of 500 points length) of the vessels' trajectories and in some cases, they zoom on the area, where the patterns have been detected. Among the most characteristic patterns that have been detected are the creeping line of the vessel SIEM PILOT, which is displayed in Figure 6(a) and the double sector pattern of the vessel VOS HESTIA, which is displayed in Figure 6(b). Two more interesting plots that demonstrate the ability of the scale down algorithm to compress the trajectory without loosing information and to capture the part of the trajectory that contains the actual pattern are depicted in Figure 8. The left plot shows a chunk from the trajectory of SIEM PILOT \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Bearing**} & \multicolumn{6}{c}{**Mixed (Bearing \& Bearing \& Change)**} \\ \hline
**SAR Pattern** & **BA** & **DGN** & **PHO** & **SP** & **VH** & **BA** & **DGN** & **PHO** & **SP** & **VH** \\ \hline Steps (L) & 2 & 5 & 4 & 8 & 0 & 1 & 8 & 4 & 8 & 2 \\ Steps (R) & 4 & 8 & 8 & 2 & 10 & 3 & 6 & 2 & 6 & 2 \\ Spiral (L) & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 4 & 0 & 1 \\ Spiral (R) & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ Expanding square (L) & 1 & 2 & 3 & 4 & 1 & 0 & 2 & 0 & 2 & 2 \\ Expanding square (R) & 1 & 3 & 1 & 4 & 1 & 0 & 0 & 0 & 0 & 0 \\ Creeping line (L) & 2 & 1 & 0 & 3 & 1 & 0 & 0 & 0 & 0 & 0 \\ Creeping line (R) & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \\ Sector (L) & 3 & 0 & 1 & 4 & 1 & 0 & 0 & 0 & 3 & 0 \\ Sector (R) & 5 & 3 & 3 & 4 & 2 & 0 & 0 & 0 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Number of trajectory segments where SAR patterns have been detected, using bearing only and bearing together with bearing change (mixed). Figure 7: Selected plots from real trajectories that have been classified to SAR patterns. that has been classified as creeping line. The zoom on the right plot, actually reveal that at the detect trajectory segment the vessel was actually performing some SAR maneuvers. Although there is enough distortion, probably because of the weather and the sea currents in the area, the creeping line pattern is still visible. Figures 7 and 8 demonstrate some correct predictions of the proposed technique.