Chapter 4 - Subjective and objective quality assessment for omnidirectional video

Abstract

Video quality assessment is generally important to assess any kind of immersive media technology, for example, to evaluate a captured content, algorithms for encoding and projection, and systems, as well as for technology optimization. This chapter provides an overview of the two types of video quality assessment, subjective testing with human viewers, and quality prediction or estimation using video quality metrics or models. First, viewing tests with humans as the gold standard for video quality are reviewed in light of their instantiation for omnidirectional video (ODV). In the second part of the chapter, the less time-consuming, better scalable second type of assessment with objective video quality metrics and models is discussed, considering the specific requirements of ODV. Often they incorporate computational models of human perception and content properties. ODV introduces the challenges of interactivity compared to standard 2D video and typically spherical projection distortions due to its omnidirectional, “point-of-view” (in terms of camera-shot type) nature. Accordingly, subjective tests for ODV include specific considerations of the omnidirectional nature of the presented content and dedicated head-rotation or even additional eyetracking data capture. In the last part of the chapter, it is shown how to improve objective video quality prediction by taking into account user behavior and projection distortions.