# Supervised Learning Based Peripheral Vision System for
## 4 Experiments and Results
### User Study
In case of Ocean data set, the mean score varied from 2 to 3 from Effect 1 to Effect 2, which depicts the overall disagreement to the sickness. For Q3 and the forest data set, the mean score changes from 4 to 5 from Effect 1 to Effect 2, which depicts that the user was impressed by watching the Effect 2 video. Furthermore, the mean score for the Ocean dataset remains same showing that user was impressed equally watching the videos of both the effects. For Q4 and both the data sets, the mean score remains unchanged from Effect 1 to Effect 2, which indicates that the user felt present watching both the effect videos. For Q5 and the forest data set, the mean score changes from 4 to 5 from Effect 1 to Effect 2, which shows that the Effect 2 experience was comfortable. In case of Ocean dataset, the mean score remains constant indicating that the both the effects were comfortable. For Q6 and the two datasets, the mean score changes from 2 to 5 from Effect 1 to Effect 2, showing that the inside and outside of the TV were connected for Effect 2. We also conducted interviews from the participants, and we observed that there was a difference of opinion among the participants about the proposed system. For the case of Q1 (enjoyment) and Q2 (sickness), different opinions were recorded as follows:  
* \"I really enjoyed the videos. This effect can be used in cinemas and living room to enhance the visual experiences.\" (positive comment),
* \"The videos give dizziness or sickness feeling, either it's going too fast or something else is an issue.\" (negative comment). Similarly, we observed different comments for the case of Q3 (Emotion) and Q4 (Immersion) as follows: \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Measurement**} & \multirow{2}{*}{**Dataset**} & \multicolumn{6}{c}{**Questions**} \\  & & **Q1** & **Q2** & **Q3** & **Q4** & **Q5** & **Q6** \\ \hline M & Forest Effect 1 & 3 & 3 & 4 & 5 & 4 & 2 \\ E & Forest Effect 2 & 5 & 3 & 5 & 5 & 5 & 5 \\ A & Ocean Effect 1 & 5 & 2 & 5 & 5 & 5 & 2 \\ N & Ocean Effect 2 & 5 & 3 & 5 & 5 & 5 & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The user study results for the Forest and Ocean Videos with Effect 1 and Effect 2. Figure 12: The graphs generated after performing user study for the Ocean and Forest dataset for Effect 1 and Effect 2 (**a**) Graphs for Forest Effect 1 (**b**) Graphs for Forest Effect 2 (**c**) Graphs for Ocean Effect 1 (**d**) Graphs for Ocean Effect 2 and (**e**) Questions for user study. * \"Colors are vibrant and stimulating. The illumination seems great making visual experiences immersive and entertaining.\" (positive comment),
* \"The projector resolution seems low disturbing the feeling of emotion and immersion.\" (negative comment). For Q5 (Comfort), the positive and negative comments are as follows:
* \"The effects are enchanting and attractive.\"(positive comment),
* \"The visual experience causes some kind of flicker movement.\"(negative comment). Consistency (Q6) is considered to be very important consideration for this kind of user study. Negative and positive opinions were recorded for the case of consistency, which are as follows:  
* \"The contrast as well as the resolution seems enhanced. The bigger screen immerses the user fully in the scene, while the smaller screen focuses on the content and delivering the information.\"
* \"There is a synchronization problem between the video on TV and projected content as the projected video is slower than the one playing on TV, it's hard to relate to both at a time.\"  
The analysis from the interviews of the participants reveals some kind of problems, such as sickness, flicker, inadequate projector resolution, and some synchronization problems. The experience can be enhanced by using Nvidia's DLSS (Deep Learning Super Sampling) approach to provide high resolution data to the projector to tackle low resolution problem. Flicker problem can be removed by including temporal correlation in the PCE architecture. We only included the spatial correlation in the PCE network.