Enhancing TMIV Performance Through Proximity-Aware Grouping and Preservation of Small Clusters

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 $5.12 \%$.

Authors

Institutions

Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icip51287.2024.10647454
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing TMIV Performance Through Proximity-Aware Grouping and Preservation of Small Clusters

Ahmad Vakili, Stéphane Coulombe, Mohammadreza Jamali, Carlos Vázquez et al.
Energy Efficient Wireless Sensor Networks
article

Enhancing TMIV Performance Through Proximity-Aware Grouping and Preservation of Small Clusters

Ahmad Vakili, Stéphane Coulombe, Mohammadreza Jamali, Carlos Vázquez, Mahshad MahdaviMoghadam
article en

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 $5.12 \%$.

Guilford Technical Community College (US), École de Technologie Supérieure (CA)
Mitacs
Openalex Percentile: Top 82%
Energy Efficient Wireless Sensor Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.