# Correlation between Human Emotion and Temporal-Spatial Contexts by Analyzing Environmental Factors
## 4 Experiments and Results
As a result, we could construct a total of 15 combinations as shown in Table 1.  
Finally, the comparison analysis was performed using all nine features for a total of 15 cases, as shown in Table 2. Through the comparison analysis, we confirmed that the method of using all nine features is more effective in terms of the RMS error compared to three cases by using single, double, and triple features, respectively. In addition, we confirmed that using the multi-features method is more efficacious than the other methods for analyzing the impact of the combination of different factors in the surrounding environment on people. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \begin{tabular}{c} **Timei** \\ **Complexity** \\ **(\#1)** \\ \end{tabular} & \begin{tabular}{c} **Spatial Complexity** \\ **(\#2, \#3)** \\ \end{tabular} & \
\begin{tabular}{c} **Colors** \\ **(\#4, \#5, \#6, \#7)** \\ \end{tabular} &
\begin{tabular}{c} **Sounds** \\ **(\#8, \#9)** \\ \end{tabular} \\ \hline \multirow{4}{*}{1 feature} & 1 & O & & & \\  & 2 & & O & & \\  & 3 & & & O & \\  & 4 & & & O & \\ \hline \multirow{4}{*}{2 features} & 5 & O & O & & \\  & 6 & O & & O & \\  & 7 & O & & & O \\  & 8 & & O & O & \\  & 9 & & O & O & O \\  & 10 & & & O & O \\ \hline \multirow{4}{*}{3 features} & 11 & O & O & O & \\  & 12 & O & O & & O \\  & 13 & O & O & O & O \\  & 14 & & O & O & O \\ \hline \multirow{4}{*}{4 features} & 15 & O & O & O & O \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The analyses for 15 combinations from single feature to multi features. For the root mean square (RMS) error analysis of the dataset results, the error was represented as approximately 0.213 and 0.272 for the \"Pleasant-Unpleasant\" and \"Arousal-Relaxation\" categories, respectively. Furthermore, the average RMS error was 0.347 in the two-dimensional emotional plane. In other words, the distance of one diagonal line was approximately 0.35 when the two-dimensional region was divided into 3 \(\times\) 3 grids, as shown in Figure 10.  
Consequently, the results between the subjectively evaluated emotion and the estimated emotion can be assumed to be in the same position in one column because the mean distance deduced from this study was estimated to be \(\pm\)0.48. Based on this observation, we confirmed that the error results are within 12.5% of the result deduced by the SVR and the results of the actual human subjective evaluation of the 2D emotional plane. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Time** & **Spatial Complexity** & **Colors** & **Sounds** \\
**Complexity** & **(\#1)** & **(\#2, \#3)** & **(\#4, \#5, \#6, \#7)** & **(\#8, \#9)** \\ \hline \multirow{8}{*}{Analysis results} & X & Y & RMS error \\
1 & 0.216483 & 0.27832 & 0.352601 \\
2 & 0.223818 & 0.306747 & 0.379721 \\
3 & 0.248052 & 0.278794 & 0.37317 \\
4 & 0.218412 & 0.292037 & 0.364677 \\
5 & 0.25667 & 0.273287 & 0.37492 \\
6 & 0.214291 & 0.291447 & 0.361749 \\
7 & 0.22879 & 0.325893 & 0.398185 \\
8 & 0.233288 & 0.28422 & 0.367702 \\
9 & 0.220008 & 0.279171 & 0.55443 \\
10 & 0.252436 & 0.409451 & 0.481013 \\
11 & 0.292138 & 0.29055 & 0.411676 \\
12 & 0.270467 & 0.284067 & 0.392233 \\
13 & 0.214582 & 0.272132 & 0.355443 \\
14 & 0.289204 & 0.28018 & 0.396813 \\
**15** & **0.21276** & **0.271701** & **0.346556** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison analyses using all 15 cases. Figure 10: The distance of results between estimated emotion and subjective evaluation on the 2D emotional plane divided into a 3 \(\times\) 3 grid.