VOLVQAD: An MPEG V-PCC Volumetric Video Quality Assessment Dataset

Samuel Rhys Cox, May Lim, Wei Tsang Ooi

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

4 Citations (Scopus)

Abstract

We present VOLVQAD, a volumetric video quality assessment dataset consisting 7,680 ratings on 376 video sequences from 120 participants. The volumetric video sequences are first encoded with MPEG V-PCC using 4 different avatar models and 16 quality variations, and then rendered into test videos for quality assessment using 2 different background colors and 16 different quality switching patterns. The dataset is useful for researchers who wish to understand the impact of volumetric video compression on subjective quality. Analysis of the collected data are also presented in this paper.
Original languageUndefined/Unknown
Title of host publicationProceedings of the 14th Conference on ACM Multimedia Systems (MMSys'23)
Publication date7 Jun 2023
DOIs
Publication statusPublished - 7 Jun 2023
Externally publishedYes

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