## 4 Results
### Performance of the Proposed Model  
To analyse the performance of the proposed DEC measurement-based no-reference quality evaluation model for providing accurate assessment of the rendered view quality, a logistic regression-based comparison has been designed using the video sequences from the dataset. Table 3 presents the logistic regression statistics for the results of both 2D MOS and DEC measurement-based model that are grouped by the utilised colour sequence.  
The DEC measurement-based model's good performance can be noticed from most results reported in the table, i.e., offering high correlation and low error readings. However, a variation in the performance level of the model can also be noted between different sequences. This observation can be explained by the fact that depth map performance is dependent on the colour sequence used in the rendering process. As such, the different spatio-temporal information levels present in the video sequences have an influence on the overall quality performance, as was also noted in a previous section. For example, the _BMX_ and _Musicians_ sequences are characterised as high texture and motion video contents. Therefore, the different quality depth maps used in the rendering process has a major impact on the perceived quality of the rendered overall view. On the other hand, the _Parisband_ sequence has low spatio-temporal information characteristics. Thus, variation in the quality of the rendered depth maps has less of a noticeable effect on the perceived quality of the rendered view. In other words, rendered views from sequences with low texture complexities and little motion content are more immune to errors in the depth map used in the rendering process.  
Despite the regression results for the _Parisband_ sequence offering low correlation, the adopted DEC measurement-based model outperforms the traditional objective quality assessment methods. Table 4 shows the regression results between the 2D MOS values and VQM when considered per sequence. VQM is taken as an example here, since it is the top-performing objective quality method out of all the traditional objective quality methods assessed in our experiments. It is clearly evident from the comparison of both Tables 3 and 4 that the adopted DEC measurement-based model outperforms VQM results with respect to all of the considered sequences, including the _Parisband_ sequence.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & **2D MOS** & **DEC** & [27] & [28] & [24] & [25,26] & [29] & [30] \\ \hline HRM & 1 & 1 & 8 & 9 & 1 & 8 & 4 & 8 \\ DERS\_OFF & 2 & 2 & 10 & 10 & 1 & 9 & 2 & 9 \\ DERS\_ON & 3 & 3 & 9 & 6 & 1 & 10 & 1 & 10 \\ RSGM\_FIL & 4 & 5 & 4 & 4 & 7 & 4 & 3 & 5 \\ ST & 5 & 4 & 5 & 3 & 1 & 2 & 6 & 6 \\ NL & 6 & 6 & 7 & 5 & 1 & 6 & 8 & 7 \\ GF & 7 & 7 & 3 & 8 & 6 & 5 & 10 & 3 \\ RSGM & 8 & 9 & 1 & 7 & 7 & 7 & 7 & 1 \\ RSGM\_GAUS & 9 & 8 & 6 & 1 & 10 & 1 & 9 & 4 \\ RSGM\_SCAN & 10 & 10 & 2 & 2 & 7 & 3 & 5 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Ranking table for MOS and no-reference quality evaluation methods (DEC: Proposed model).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **CC** & **SSE** & **RMSE** \\ \hline _Band_ & 0.94015 & 0.019771 & 0.044640 \\ _BMX_ & 0.97630 & 0.004586 & 0.022573 \\ _Musicians_ & 0.95858 & 0.013428 & 0.036644 \\ _Poker_ & 0.89905 & 0.079153 & 0.088968 \\ _Act_ & 0.84098 & 0.056247 & 0.089639 \\ _Parisband_ & 0.32950 & 0.133540 & 0.138120 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Logistic regression statistics for DEC measurement-based model per sequence.