3D Video Quality Assessment

TL;DR

This paper discusses the importance of assessing 3D video quality, highlighting the challenges of subjective testing and proposing the development of objective metrics, including no-reference and full-reference methods, to evaluate perceptual quality effectively.

Contribution

The paper introduces a framework for 3D video quality assessment, emphasizing the need for no-reference and full-reference objective metrics to improve quality evaluation.

Findings

Subjective tests are impractical for routine quality assessment.

Objective metrics can model the Human Visual System for better evaluation.

No-reference metrics are useful for capturing parameters, while full-reference metrics aid in resource management.

Abstract

A key factor in designing 3D systems is to understand how different visual cues and distortions affect the perceptual quality of 3D video. The ultimate way to assess video quality is through subjective tests. However, subjective evaluation is time consuming, expensive, and in most cases not even possible. An alternative solution is objective quality metrics, which attempt to model the Human Visual System (HVS) in order to assess the perceptual quality. The potential of 3D technology to significantly improve the immersiveness of video content has been hampered by the difficulty of objectively assessing Quality of Experience (QoE). A no-reference (NR) objective 3D quality metric, which could help determine capturing parameters and improve playback perceptual quality, would be welcomed by camera and display manufactures. Network providers would embrace a full-reference (FR) 3D quality metric, as they could use it to ensure efficient QoE-based resource management during compression and Quality of Service (QoS) during transmission.