Estimation of optimal encoding ladders for tiled 360{\deg} VR video in adaptive streaming systems
Cagri Ozcinar, Ana De Abreu, Sebastian Knorr, Aljosa Smolic

TL;DR
This paper introduces a content-aware method for estimating optimal encoding ladders for tiled 360-degree VR videos in adaptive streaming, improving quality and resource efficiency over existing standards.
Contribution
It proposes a novel encoding ladder estimation approach using content features, distortion and resource models, and an ILP algorithm considering practical constraints.
Findings
Outperforms professional service provider encoding ladders in objective quality.
Provides cost-effective encoding solutions tailored to VR content.
Enhances immersive streaming experiences with optimized resource use.
Abstract
Given the significant industrial growth of demand for virtual reality (VR), 360{\deg} video streaming is one of the most important VR applications that require cost-optimal solutions to achieve widespread proliferation of VR technology. Because of its inherent variability of data-intensive content types and its tiled-based encoding and streaming, 360{\deg} video requires new encoding ladders in adaptive streaming systems to achieve cost-optimal and immersive streaming experiences. In this context, this paper targets both the provider's and client's perspectives and introduces a new content-aware encoding ladder estimation method for tiled 360{\deg} VR video in adaptive streaming systems. The proposed method first categories a given 360{\deg} video using its features of encoding complexity and estimates the visual distortion and resource cost of each bitrate level based on the proposed…
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Taxonomy
TopicsImage and Video Quality Assessment · Video Coding and Compression Technologies · Multimedia Communication and Technology
