## 4 Results
### Validating the Accuracy of the Proposed DEC Measurement-Based Model  
To validate the accuracy of the developed model fit from Section 3.1.2, a symmetrical logistic function is used to obtain the regression statistics. Figure 10a,b present the logistic regression results for both the training and testing sets of the 2D video subjective assessment. For this purpose, the available 2D MOS subjective assessment dataset has been divided equally into the training and testing sets, as mentioned previously.  
The correlation coefficients obtained for both sets are high, and the low RMSE values point at the high accuracy of the trained model in predicting the quality of the views rendered utilising the available depth maps. The correlation results also demonstrate superior performance when compared to the correlation results obtained for the 2D full-reference objective quality assessment methods, whose results have been presented in the previous section (Section 4.2). For further validation of the developed DEC measurement-based no-reference quality evaluation model, Figure 10c presents the logistic regression results between the model based MOS values and 3D video subjective assessment. These results are consistent with the results obtained in the training and testing phases of the developed quality evaluation model.  
Further validation of the DEC measurement-based model's results calls for a comparison with the results of the conventional no-reference quality evaluation methods discussed in Section 2.2. For this, all of the methods have been compared utilising their available implementations for research purposes [48]. All of the results presented here have been obtained using the same testing set across all experiments without the influence of the training set that was used to build and calibrate our model initially. It is worth noting that these methods are designed to assess the quality of the rendered views directly, rather than assessing the quality of the depth maps used in the rendering process as advocated in our research. The correlation between the aforementioned methods and 2D MOS results is very low. Table 2 demonstrates the lack of correlation by presenting the results of the different methods with respect to the views rendered using various depth maps for the _Poker_ colour sequence. In contrast, the proposed DEC measurement-based model results correlate well with the recorded real user MOS results (taken as the ground truth for this experiment, as listed in the second column of the table). A variety of depth map production techniques (as listed in the first column of the table) were involved during the subjective tests where the MOS values were recorded. To simplify the understanding of the results, the table is presented in ranking order. As such, each score has been converted to rank for all the methods tested across the board, and they are aligned according to the 2D MOS values in the table. Similar results have been obtained using all video test sequences available in the dataset.  
Figure 9: Visual comparison between the rendered views of the _Musicians_ sequence: (**a**) View rendered utilising RSGM_GAUS depth map; (**b**) view rendered utilising RSGM_SCAN depth map.  
Figure 10: MOS logistic regression results: (**a**) 2D training set results; (**b**) 2D testing set results; (**c**) 3D MOS logistic regression results.