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

Abstract

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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 $5.12 \%$.