Crowdsourced subjective 3D video quality assessment

Abstract

This article proposes a new method for subjective 3D video quality assessment based on crowdsourced workers—Crowd3D. The limitations of traditional laboratory-based grade collection procedures are outlined, and their solution through the use of a crowd-based approach is described. Several conceptual and technical requirements of crowd-based 3D video quality assessment methods are identified and the solutions adopted described in detail. The system built takes the form of a web-based platform that supports 3D video monitors, and orchestrates the entire process of observer validation, content presentation and quality, depth, and comfort grade recording in a remote database. The crowdsourced subjective 3D quality assessment system uses as source contents a set of 3D video and grades database assembled earlier in a laboratory setting. To evaluate the validity of the crowd-based approach, the grades gathered using the crowdsourced system were analysed and compared to a set of grades obtained in laboratory settings using the same data set. Results show that it is possible to obtain Pearson’s and Spearman’s correlation up to 0.95 for quality Difference Mean Opinion Score and 0.96 for quality Mean Opinion Score, when comparing with laboratory grades. Apart from the present study, the 3D video quality assessment platform proposed can be used with advantage for further related research activities, reducing the time and cost compared to the traditional laboratory-based quality assessments.