No-Reference Depth Map Quality Evaluation Model Based on Depth Map Edge Confidence Measurement in Immersive Video Applications

Abstract

When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. 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 model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance.

Multimedia Quality of Experience (QoE): Current Status and Future Direction

“…As a solution, this study proposes an encoding framework that is capable of generating video bit streams with arbitrary bit rate and decoding complexity levels using a decoding complexity rate distortion model. Safak Dogan, Nasser Haddad, Erhan Ekmekcioglu and Ahmet M. Kondoz are the authors of the fourth paper [9], which focuses on multi-view 3D content with dense depth map information. In this paper, the authors present a no-reference depth map quality evaluation model based on a novel depth map edge confidence measurement technique, in order to assist with the estimation of the quality of virtual views in multi-view video content.…”