IV-PSNR—The Objective Quality Metric for Immersive Video Applications

Dziembowski, Adrian; Mieloch, Dawid; Stankowski, Jakub; Grzelka, Adam

doi:10.1109/tcsvt.2022.3179575

Cited by 36 publications

(20 citation statements)

References 86 publications

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“…An objective quality metric for assessing the quality of synthesized views for virtual reality applications is the IV-PSNR (Immersive Video -Peak Signal to Noise Ratio). 19,20 Unlike traditional PSNR metric that is commonly used for visual content assessments, this metric offers a better quality evaluation of synthesized images as it deals with two typical immersive video distortions: the pixel shift and the global component difference. IV-PSNR is an objective quality metric like PSNR calculating the difference between corresponding pixels, but in IV-PSNR a matching window with slight left/right-up/down shifts maximizes the pixel match, prior to calculating the pixels' difference, accounting for possible image shifts that may occur when synthesizing a virtual view.…”

Section: Quality Evaluationmentioning

confidence: 99%

Assessment of multi-plenoptic 2.0 camera depth maps for DIBR

Khosroshahi

Sancho

Rosa

et al. 2023

International Workshop on Advanced Imaging Technology (IWAIT) 2023

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We aim to evaluate the depth map quality by the plenoptic 2.0 cameras for DIBR applications, by simulating a multi-plenoptic camera array, and synthesizing virtual images based on the obtained color and depth maps. The real-time generated depth maps by plenoptic cameras are compared with the offline and high-quality depth maps estimated by the MPEG-I Depth Estimation Reference Software (DERS). Results show that synthesized virtual image quality obtained by RGBD plenoptic cameras has acceptable quality for real-time DIBR applications, but lower than using the depth estimated by DERS, due to a loss of inter-view depth consistency.

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Section: Quality Evaluationmentioning

confidence: 99%

Assessment of multi-plenoptic 2.0 camera depth maps for DIBR

Khosroshahi

Sancho

Rosa

et al. 2023

International Workshop on Advanced Imaging Technology (IWAIT) 2023

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“…Furthermore, the MIV-CTC defines the methodology to assess objective and subjective quality. Objective quality is evaluated using two full-reference quality metrics: WS-PSNR [21] and IV-PSNR [22]. These metrics measure the quality of synthesized source views by calculating BD rates [23].…”

Section: Video Coding and Quality Assessmentmentioning

confidence: 99%

The MPEG Immersive Video Standard—Current Status and Future Outlook

Vadakital¹,

Dziembowski

Lafruit

et al. 2022

IEEE MultiMedia

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The MPEG immersive video (MIV) standard is the latest addition to the MPEG-I suite of standards.It focuses on the representation and coding of immersive media. MIV is designed to support virtual and extended reality (VR/XR) applications that require six degrees of freedom (6DoF) visual interaction with the rendered scene. Edition-1 of MIV is now in its final phase of standardization. Leveraging conventional 2D video codecs, the MIV standard efficiently codes volumetric scenes and allows advanced visual effects like bullet-time flythroughs. The video feeds capturing the scene are first processed to identify a set of basic views that are augmented with additional information from all other views. The data is then intelligently packed into atlases and further compressed with any existing 2D video codec of choice. Experimental results show BD-PSNR gains of up to 6 dB in the 10 to 20 Mbps range compared to a naive simulcast multiview video coding approach. The paper concludes with an outlook on future extensions for the second edition of MIV.

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“…As the VVenC version v0.1.3.0, which is listed in the CTC, does not support subpictures, this experiment used the recent version of VVenC. The immersive video peak signal-to-noise ratio (IV-PSNR) is an end-to-end quality metric suitable for 6DoF immersive video quality assessment and which was used in this experiment [37]. A modified version of SubpicMergeApp in VTM version v11.0 conducted subpicture merging, and the modifications are explained in Section IV.…”

Section: A Experimental Conditionsmentioning

confidence: 99%

VVC Subpicture-Based Frame Packing for MPEG Immersive Video

2022

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The moving picture experts group (MPEG) video coding group started an immersive video coding standard project to accomplish acceptable bandwidth and decoding resources for multiple immersive videos with texture (color) and geometry (depth) information. The MPEG immersive video (MIV) coding standard provides functionality to remove inter-view redundancy and merge the residuals into videos defined as atlases. Although MIV reduces the number of videos to decode, an efficient decoder instance reduction method has not been investigated. This study proposes a frame packing implementation in MIV software. The proposed method conducts frame packing for geometry atlases to align with texture atlases, encodes them as subpicture bitstreams, and merges one texture / geometry atlas into a single bitstream with a bitstream merger. Furthermore, the proposed method provides control over the number of decoder instances without significantly increasing the computational complexity compared to existing frame packing methods. Therefore, the proposed method was accepted in MIV and will be implemented on the recent version of the reference software of MIV.

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IV-PSNR—The Objective Quality Metric for Immersive Video Applications

Cited by 36 publications

References 86 publications

Assessment of multi-plenoptic 2.0 camera depth maps for DIBR

Assessment of multi-plenoptic 2.0 camera depth maps for DIBR

The MPEG Immersive Video Standard—Current Status and Future Outlook

VVC Subpicture-Based Frame Packing for MPEG Immersive Video

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