ENHANCING TMIV PERFORMANCE THROUGH PROXIMITY-AWARE GROUPING AND PRESERVATION OF SMALL CLUSTERS

Research output: Contribution to Book/Report typesContribution to conference proceedingspeer-review

Abstract

Virtual reality applications possess significant societal potential, capable of revolutionizing user experiences and generating substantial revenue. However, their high demand for bit rates poses significant challenges. The MPEG Immersive Video (MIV) standard, an integral component of MPEG-I, is designed to efficiently compress visual content from multiple cameras by pruning redundant information. This article proposes a new method to enhance the compression efficiency of MIV by grouping and preserving small clusters of non-pruned pixels that would otherwise be discarded in the default configuration of the Test Model for Immersive Video (TMIV). Experimental results demonstrate that the proposed method attains an average Bjøntegaard-Delta bitrate (BD-BR) reduction of 3.35% across six tested sequences when compared to TMIV with the default configuration. Notably, one of them exhibits a reduction reaching 5.12%.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Image Processing, ICIP 2024 - Proceedings
PublisherIEEE Computer Society
Pages3375-3381
Number of pages7
ISBN (Electronic)9798350349399
DOIs
Publication statusPublished - 2024
Event31st IEEE International Conference on Image Processing, ICIP 2024 - Abu Dhabi, United Arab Emirates
Duration: 27 Oct 202430 Oct 2024

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference31st IEEE International Conference on Image Processing, ICIP 2024
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period27/10/2430/10/24

!!!Keywords

  • MPEG Immersive Video
  • Test Model for Immersive Video
  • Virtual reality
  • video compression

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