Quality Assessment of DIBR-synthesized views: An Overview

PubDate: Nov 2019

Teams: Shenzhen University；National Institute of Applied Sciences of Rennes；Shenzhen
Institutes of Advanced Technology

Writers: Shishun Tian, Lu Zhang, Wenbin Zou, Xia Li, Ting Su, Luce Morin, Olivier Deforges

PDF: Quality Assessment of DIBR-synthesized views: An Overview

Abstract

The Depth-Image-Based-Rendering (DIBR) is one of the main fundamental technique to generate new views in 3D video applications, such as Multi-View Videos (MVV), Free-Viewpoint Videos (FVV) and Virtual Reality (VR). However, the quality assessment of DIBR-synthesized views is quite different from the traditional 2D images/videos. In recent years, several efforts have been made towards this topic, but there lacks a detailed survey in literature. In this paper, we provide a comprehensive survey on various current approaches for DIBR-synthesized views. The current accessible datasets of DIBR-synthesized views are firstly reviewed. Followed by a summary and analysis of the representative state-of-the-art objective metrics. Then, the performances of different objective metrics are evaluated and discussed on all available datasets. Finally, we discuss the potential challenges and suggest possible directions for future research.