## 1 Introduction  
Research into immersive video applications in the televised digital media domain has attracted growing attention in recent years. Such video applications include three-dimensional television (3 DTV) [1] and free-viewpoint television (FTV) [2] with inclusive quality of experience (QoE) offering. Multi-view video (MVV) is a video format that allows for truly immersive user experiences with its support for navigating through multiple viewpoints in those immersive video applications [3]. However, the broadcast of high-quality MVV content stretches the bandwidth resource requirements significantly. Depth image-based rendering (DIBR) is used as a remedy to allow for creating virtual camera views at the receiver end, eliminating the need for transmitting a large number of real viewpoints [4]. Thus, the quality and accuracy of the information present in-depth maps and their ability to render the required views have become the subject of much greater scrutiny in multimedia research. Several challenges arise when assessing the quality of depth maps, such as the lack of a suitable reference for comparing the available depth maps, especially when it comes to live content.  
In a typical 3 DTV or FTV immersive video application, the lack of reference has a twofold effect: No reference for the resulting rendered colour views and no reference for the depth maps used in the rendering process. DIBR aims to render virtual views at locations where no original real view exists, i.e., completely new camera viewing angles, to enhance user QoE in these immersive video applications. This means that a rendered virtual view is at a different location (angle) with respect to any of the original colour views, which does not offer an accurate comparison if taken as a reference, as the two views contain different information of the same scene. An example of the original colour views and desired rendered virtual view locations are depicted in Figure 1.  
Similarly, the lack of a suitable reference for a depth map corresponding to the rendered virtual colour view poses a challenge. Traditionally in computer vision applications, evaluation of the accuracy of depth maps has been performed using high precision \"ground truth\" depth maps as a reference [5; 6]. These are very accurate representations of the 3D geometry information of their associated colour views. The presence of a ground truth depth map provides a reliable measure of the accuracy of the depth maps produced through depth/disparity (stereo-matching) algorithms [7; 8; 9; 10; 11; 12]. However, ground truth depth maps are very complex and time-consuming to produce and are only viable when the scene in view is controlled in terms of size and depth. They are not easily accessible for high-quality natural scenes. Further, ground truth depth maps cannot be produced for live broadcast containing high-quality and dynamic content scenes that are typically used in 3 DTV/FTV immersive video applications.  
As the quality of the overall rendered views is also dictated by the contribution of their depth component, the quality of the depth maps utilised in the rendering process is a significant parameter for attention. Thus, this paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The rest of the paper is organised as follows. The second section introduces the background and related work. The third section focuses on the methods used to develop the depth map quality evaluation model. The fourth section presents the results obtained from the tests conducted using this newly developed model. The fifth section discusses the presented results in detail, while the sixth section concludes the paper.