Advances in video coding and networking technologies have
paved the way for the Multi-View Video (MVV) streaming.
However, large amounts of data and dynamic network conditions
result in frequent network congestion, which may prevent
video packets from being delivered on time. As a consequence,
the 3D viewing experience may be degraded signifi-
cantly, unless quality-aware adaptation methods are deployed.
There is no research work to discuss the MVV adaptation of
decision strategy or provide a detailed analysis of a dynamic
network environment. This work addresses the mentioned issues
for MVV streaming over HTTP for emerging multi-view
displays. In this research work, the effect of various adaptations
of decision strategies are evaluated and, as a result, a
new quality-aware adaptation method is designed. The proposed
method is benefiting from layer based video coding in
such a way that high Quality of Experience (QoE) is maintained
in a cost-effective manner. The conducted experimental
results on MVV streaming using the proposed strategy are
showing that the perceptual 3D video quality, under adverse
network conditions, is enhanced significantly as a result of the
proposed quality-aware adaptation.
History
School
Loughborough University London
Published in
IEEE International Conference on Acoustics, Speech, and Signal Processing
Citation
OZCINAR, C., EKMEKCIOGLU, E. and KONDOZ, A., 2016. Quality-aware adaptive delivery of multi-view video. IN: IEEE 41st International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, 20-25 March 2016, pp. 1397 - 1401.