# Networking for Cloud Robotics: The DewROS Platform and Its Application
## 6 Experimental Evaluation
### Analysis of Labels Detected  
We begin by examining the effect of the video resolution on the label detection feature of CVI and AR, using three videos, all representing avalanche scenarios and converted to High Definition (1080p and 720p) and Standard Definition (360p and 240p) resolutions. As depicted in Figure 5 for CVI, a trend can be distinguished in the number of labels found at different resolutions, i.e., the lower the resolution, the higher the number of labels. There are some reasons that can explain this tendency. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Network** & **Label** & \multicolumn{2}{c}{**Video Type**} & **Video** \\ \cline{3-5}
**Connection** & **Detection Mode** & **Size** & **Length** & **Location** \\ \hline University & \multirow{2}{*}{Unspecified} & Small & Short & Local \\ Ethernet & & (2.1 MB—52 s) & (2.1 MB—3 s) & (LOC) \\ (UNI) & & & & \\ \hline Residential & \multirow{2}{*}{Shot \& Frame} & Medium & Long & Google \\ FTTH & & (8.8 MB—53 s) & (2.2 MB—71 s) & Cloud Storage \\ (HOME) & & & & (GCS) \\ \hline Satellite & \multirow{2}{*}{\
\begin{tabular}{c} Large \\ (SAT) \\ \end{tabular} } & Large & \multirow{2}{*}{
\begin{tabular}{c} \\ (23.7 MB—55 s) \\ \end{tabular} } & \\ \cline{1-1} \cline{3-5}  & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Details of the variables considered in the experiments. Figure 5: Number of labels obtained at different video resolutions for CVI. The cloud service can generate many non-pertinent labels for each erroneous entity detected in a video, namely, an object or an action that does not appear in the video. Moreover, there is a higher probability that CVI returns more erroneous labels on low-resolution videos than on high-resolution ones. This has been investigated by extracting the labels in the _Shot & Frame_ mode from the three videos A, B, and C, and inspecting them manually. A striking case of the above considerations is represented in Figure 6, where the labels returned by CVI for video C, with the lowest and the highest considered resolution, are reported. The labels that appear in only one resolution are represented by boxes with solid borders, while the non-pertinent ones are represented by dashed borders.It can be noticed that the service confuses the skiing action at high speed on a white background with parachuting, returning about 15 labels associated with that error. The erroneous labels decrease gradually with increasing resolution until they disappear completely at 1080p. Another element influencing the number of labels obtained is that low-resolution videos contain more irrelevant labels, namely, labels not adding useful information, or those quite similar to others. In conclusion, the higher number of labels obtained at lower resolutions could be due to both non-pertinent labels associated with incorrect interpretations of video contents and irrelevant labels. However, video C represents a case in point, where the cloud service fails to detect an entity in the background. In the other two videos, it seems that the resolution is not determinant of the success of the task, since erroneous detection or labels adding valuable information at higher resolutions rather than at lower ones cannot be found. The impact of the video resolution on the confidence level of the labels was then analyzed. As described previously, the result of an annotation request is a list of labels and, for each of them, the video frames, the time it refers to and the level of confidence of such labels are also reported. Two opposite effects can be expected, depending on the pertinence of the returned labels. On one side, the level of confidence can decrease with the increasing resolution because the service becomes less certain of erroneous detection. However, the level of confidence can increase with increasing resolution because the service has a sharper view of the proper entities in the video. The trend observed in the last case is that the confidence of the proper labels remains almost unchanged, increasing the resolution.