  Immersive video offers the freedom to navigate inside virtualized
environment. Instead of streaming the bulky immersive videos entirely, a
viewport (also referred to as field of view, FoV) adaptive streaming is
preferred. We often stream the high-quality content within current viewport,
while reducing the quality of representation elsewhere to save the network
bandwidth consumption. Consider that we could refine the quality when focusing
on a new FoV, in this paper, we model the perceptual impact of the quality
variations (through adapting the quantization stepsize and spatial resolution)
with respect to the refinement duration, and yield a product of two closed-form
exponential functions that well explain the joint quantization and resolution
induced quality impact. Analytical model is cross-validated using another set
of data, where both Pearson and Spearman's rank correlation coefficients are
close to 0.98. Our work is devised to optimize the adaptive FoV streaming of
the immersive video under limited network resource. Numerical results show that
our proposed model significantly improves the quality of experience of users,
with about 9.36\% BD-Rate (Bjontegaard Delta Rate) improvement on average as
compared to other representative methods, particularly under the limited
bandwidth.
