## 5 Discussion
### Future Research Directions  
Depth map quality is a key area in developing immersive video applications, as it provides the potential for generating more views available at the receiver end without excessively utilising valuable communication bandwidth resources. As such, further research will be beneficial in the following directions. Firstly, developing a complementary measure that consists of inter-view depth confidence, coupling with the depth map quality model proposed here, is envisaged to offer a higher degree of objective quality estimation when richer MVD datasets are available for testing. The inter-view depth confidence can be explained as a per-view and per-pixel spatial confidence map that outlines the pixel positions, for which the depth value is consistent across different views. A spatial confidence map can be generated in the forward projection of the depth values of all available views into the coordinate system of a common viewpoint (i.e., the synthesised view position). This is then followed by the calculation of depth differences at every pixel location. This will provide added depth confidence measure when two reference colour views and their associated depth maps are used in the rendering process. The overall model can combine the DEC measurement presented in this paper together with inter-view confidence measurement with the prospect for predicting the quality of the resulting rendered views in much higher accuracies.  
Secondly, limitations on accurate depth data generation for wide baseline camera setups call for further research. Depth map production for wide baseline camera setups is very challenging that has been widely researched. Depth map quality has an impact on the quality of the rendered views in those camera setups. Particularly, depth quality is expected to have a more prominent impact when the target rendered view location is set at a further distance from the reference colour view than the stereoscopic distance. As such, errors in mapping colour information from the reference to the correct locations in the target view will significantly increase with the growing distance between the views. The DEC measurement-based model, together with the aforementioned inter-view depth confidence measurement, would provide a remedy to overcome inaccuracies owing to the larger view distances in-depth map quality prediction in these setups.  
Lastly, future research may involve studying the effect of utilising the developed depth map quality model as direct feedback into the depth production process, where it provides an input for the depth estimation and post-processing techniques. This can particularly be beneficial when real-time depth production process is considered for enhancing QoE of viewers in live 3 DTV/FTV immersive video applications. The advantage of such implementation would come from exploiting the DECmeasurement-based model's performance in instantly assessing depth map quality. This is essential in enabling faster and more convenient depth map production without resorting to the time and effort consuming subjective assessment methodology each time new developments into depth map production are introduced.