Multi-View Video Packet Scheduling
Laura Toni, Thomas Maugey, and Pascal Frossard

TL;DR
This paper introduces a correlation-aware packet scheduling algorithm for multiview video streaming that optimizes resource use by considering inter-camera correlations, improving multiview reconstruction quality.
Contribution
It presents a novel rate-distortion model and a low complexity trellis-based scheduling algorithm that adapts to scene content variations in multiview video transmission.
Findings
Scheduling with correlation information outperforms non-correlation-aware policies.
Increasing optimization horizon enhances transmission performance.
Correlation-aware scheduling reduces resource usage while maintaining quality.
Abstract
In multiview applications, multiple cameras acquire the same scene from different viewpoints and generally produce correlated video streams. This results in large amounts of highly redundant data. In order to save resources, it is critical to handle properly this correlation during encoding and transmission of the multiview data. In this work, we propose a correlation-aware packet scheduling algorithm for multi-camera networks, where information from all cameras are transmitted over a bottleneck channel to clients that reconstruct the multiview images. The scheduling algorithm relies on a new rate-distortion model that captures the importance of each view in the scene reconstruction. We propose a problem formulation for the optimization of the packet scheduling policies, which adapt to variations in the scene content. Then, we design a low complexity scheduling algorithm based on a…
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Taxonomy
TopicsVideo Coding and Compression Technologies · Advanced Wireless Network Optimization · Image and Video Quality Assessment
