Affordable content creation for free-viewpoint video and VR/AR applications

Pagés, Rafael; Amplianitis, Konstantinos; Monaghan, David; Ondřej, Jan; Smolić, Aljoša

doi:10.1016/j.jvcir.2018.03.012

Cited by 47 publications

(44 citation statements)

References 27 publications

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“…[21] conducted subjective evaluations with a volumetric video dataset that was acquired and released 3 , using V-PCC. Two point cloud sequences were encoded at four quality levels of geometry and color, leading to a total of 32 video sequences, that were assessed in a passive way using two subjective evaluation methodologies; that is, a side-by-side assessment of the distorted model and a pairwise comparison.…”

Section: A) Subjective Quality Assessmentmentioning

confidence: 99%

A comprehensive study of the rate-distortion performance in MPEG point cloud compression

Alexiou

Viola

Borges

et al. 2019

SIP

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Recent trends in multimedia technologies indicate the need for richer imaging modalities to increase user engagement with the content. Among other alternatives, point clouds denote a viable solution that offers an immersive content representation, as witnessed by current activities in JPEG and MPEG standardization committees. As a result of such efforts, MPEG is at the final stages of drafting an emerging standard for point cloud compression, which we consider as the state-of-the-art. In this study, the entire set of encoders that have been developed in the MPEG committee are assessed through an extensive and rigorous analysis of quality. We initially focus on the assessment of encoding configurations that have been defined by experts in MPEG for their core experiments. Then, two additional experiments are designed and carried to address some of the identified limitations of current approach. As part of the study, state-of-the-art objective quality metrics are benchmarked to assess their capability to predict visual quality of point clouds under a wide range of radically different compression artifacts. To carry the subjective evaluation experiments, a web-based renderer is developed and described. The subjective and objective quality scores along with the rendering software are made publicly available, to facilitate and promote research on the field.

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Section: A) Subjective Quality Assessmentmentioning

confidence: 99%

A comprehensive study of the rate-distortion performance in MPEG point cloud compression

Alexiou

Viola

Borges

et al. 2019

SIP

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“…To create a volumetric video quality database, we use two volumetric videos generated by the V-SENSE research group using an affordable set-up with 12 synchronised RGB cameras [3]: Two different people playing with a football as our uncompressed source videos (named 'Matis' and 'Rafa'). Sample 2D rendered versions of these two selected models are presented in Fig.…”

Section: Volumetric Video Quality Databasementioning

confidence: 99%

“…Capturing and displaying volumetric video are becoming easier with the developing technology for augmented reality (AR), mixed reality (MR), and virtual reality (VR) applications. Recent technological developments made the acquisition of volumetric video feasible [1][2][3]. The acquired volumetric video can easily be used within various AR and VR applications using the head-mounted displays (HMD).…”

Section: Introductionmentioning

confidence: 99%

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Subjective and Objective Quality Assessment for Volumetric Video Compression

Zerman¹,

Gao²,

Özçinar³

et al. 2019

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Volumetric video is becoming easier to capture and display with the recent technical developments in the acquisition, and display technologies. Using point clouds is a popular way to represent volumetric video for augmented or virtual reality applications. This representation, however, requires a large number of points to achieve a high quality of experience and needs compression before storage and transmission. In this paper, we study the subjective and objective quality assessment results for volumetric video compression, using a state-of-the-art compression algorithm: MPEG Point Cloud Compression Test Model Category 2 (TMC2). We conduct subjective experiments to find the perceptual impacts on compressed volumetric video with different quantization parameters and point counts. Additionally, we find the relationship between the state-of-the-art objective quality metrics and the acquired subjective quality assessment results. To the best of our knowledge, this study is the first to consider TMC2 compression for volumetric video represented as coloured point clouds and study its effects on the perceived quality. The results show that the effect of input point counts for TMC2 compression is not meaningful, and some geometry distortion metrics disagree with the perceived quality. The developed database is publicly available to promote the study of volumetric video compression.

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“…In FVV, actors are captured against a green screen using a multi-camera setup. For a full description of the technical pipeline see[Pagés et al 2018] …”

mentioning

confidence: 99%