  In multiview video systems, multiple cameras generally acquire the same scene
from different perspectives, such that users have the possibility to select
their preferred viewpoint. This results in large amounts of highly redundant
data, which needs to be properly handled during encoding and transmission over
resource-constrained channels. In this work, we study coding and transmission
strategies in multicamera systems, where correlated sources send data through a
bottleneck channel to a central server, which eventually transmits views to
different interactive users. We propose a dynamic correlation-aware packet
scheduling optimization under delay, bandwidth, and interactivity constraints.
The optimization relies both on a novel rate-distortion model, which captures
the importance of each view in the 3D scene reconstruction, and on an objective
function that optimizes resources based on a client navigation model. The
latter takes into account the distortion experienced by interactive clients as
well as the distortion variations that might be observed by clients during
multiview navigation. We solve the scheduling problem with a novel
trellis-based solution, which permits to formally decompose the multivariate
optimization problem thereby significantly reducing the computation complexity.
Simulation results show the gain of the proposed algorithm compared to baseline
scheduling policies. More in details, we show the gain offered by our dynamic
scheduling policy compared to static camera allocation strategies and to
schemes with constant coding strategies. Finally, we show that the best
scheduling policy consistently adapts to the most likely user navigation path
and that it minimizes distortion variations that can be very disturbing for
users in traditional navigation systems.

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