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Volume: 32 | Article ID: art00003
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Quality Assessment Protocols for Omnidirectional Video Quality Evaluation
  DOI :  10.2352/ISSN.2470-1173.2020.11.HVEI-069  Published OnlineJanuary 2020
Abstract

In recent years, with the introduction of powerful HMDs such as Oculus Rift, HTC Vive Pro, the QoE that can be achieved with VR/360° videos has increased substantially. Unfortunately, no standardized guidelines, methodologies and protocols exist for conducting and evaluating the quality of 360° videos in tests with human test subjects. In this paper, we present a set of test protocols for the evaluation of quality of 360° videos using HMDs. To this aim, we review the state-of-the-art with respect to the assessment of 360° videos summarizes their results. Also, we summarize the methodological approaches and results taken for different subjective experiments at our lab under different contextual conditions. In the first two experiments 1a and 1b, the performance of two different subjective test methods, Double-Stimulus Impairment Scale (DSIS) and Modified Absolute Category Rating (M-ACR) was compared under different contextual conditions. In experiment 2, the performance of three different subjective test methods, DSIS, M-ACR and Absolute Category Rating (ACR) was compared this time without varying the contextual conditions. Building on the reliability and general applicability of the procedure across different tests, a methodological framework for 360° video quality assessment is presented in this paper. Besides video or media quality judgments, the procedure comprises the assessment of presence and simulator sickness, for which different methods were compared. Further, the accompanying head-rotation data can be used to analyze both content- and quality-related behavioural viewing aspects. Based on the results, the implications of different contextual settings are discussed.

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Ashutosh Singla, Stephan Fremerey, Frank Hofmeyer, Werner Robitza, Alexander Raake, "Quality Assessment Protocols for Omnidirectional Video Quality Evaluationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging,  2020,  pp 69-1 - 69-7,  https://doi.org/10.2352/ISSN.2470-1173.2020.11.HVEI-069

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