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Overview and Efficiency of Decoder-Side Depth Estimation in MPEG Immersive Video.

Authors :
Mieloch, Dawid
Garus, Patrick
Milovanovic, Marta
Jung, Joel
Jeong, Jun Young
Ravi, Smitha Lingadahalli
Salahieh, Basel
Source :
IEEE Transactions on Circuits & Systems for Video Technology; Sep2022, Vol. 32 Issue 9, p6360-6374, 15p
Publication Year :
2022

Abstract

This paper presents the overview and rationale behind the Decoder-Side Depth Estimation (DSDE) mode of the MPEG Immersive Video (MIV) standard, using the Geometry Absent profile, for efficient compression of immersive multiview video. A MIV bitstream generated by an encoder operating in the DSDE mode does not include depth maps. It only contains the information required to reconstruct them in the client or in the cloud: decoded views and metadata. The paper explains the technical details and techniques supported by this novel MIV DSDE mode. The description additionally includes the specification on Geometry Assistance Supplemental Enhancement Information which helps to reduce the complexity of depth estimation, when performed in the cloud or at the decoder side. The depth estimation in MIV is a non-normative part of the decoding process, therefore, any method can be used to compute the depth maps. This paper lists a set of requirements for depth estimation, induced by the specific characteristics of the DSDE. The depth estimation reference software, continuously and collaboratively developed with MIV to meet these requirements, is presented in this paper. Several original experimental results are presented. The efficiency of the DSDE is compared to two MIV profiles. The combined non-transmission of depth maps and efficient coding of textures enabled by the DSDE leads to efficient compression and rendering quality improvement compared to the usual encoder-side depth estimation. Moreover, results of the first evaluation of state-of-the-art multiview depth estimators in the DSDE context, including machine learning techniques, are presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10518215
Volume :
32
Issue :
9
Database :
Complementary Index
Journal :
IEEE Transactions on Circuits & Systems for Video Technology
Publication Type :
Academic Journal
Accession number :
158914525
Full Text :
https://doi.org/10.1109/TCSVT.2022.3162916