How I Met Your V2X Sensor Data: Analysis of Projection-Based Light Field Visualization for Vehicle-to-Everything Communication Protocols and Use Cases
Sensors,
Journal Year:
2023,
Volume and Issue:
23(3), P. 1284 - 1284
Published: Jan. 22, 2023
The
practical
usage
of
V2X
communication
protocols
started
emerging
in
recent
years.
Data
built
on
sensor
information
are
displayed
via
onboard
units
and
smart
devices.
However,
perceptually
obtaining
such
data
may
be
counterproductive
terms
visual
attention,
particularly
the
case
safety-related
applications.
Using
windshield
as
a
display
solve
this
issue,
but
switching
between
2D
3D
reality
traffic
introduce
issues
its
own.
To
overcome
difficulties,
automotive
light
field
visualization
is
introduced.
In
paper,
we
investigate
use
cases
projection-based
technology.
Our
work
motivated
by
abundance
data,
low
latency
transfer,
availability
prototypes,
prevalent
dominance
non-autonomous
non-remote
driving,
lack
V2X-based
solutions.
As
our
primary
contributions,
provide
comprehensive
technological
review
communication,
set
recommendations
for
design
implementation,
an
extensive
discussion
implication
analysis,
exploration
utilization
based
standardized
protocols,
use-case-specific
considerations.
Language: Английский
Boosting Light Field Image Super Resolution Learnt From Single-Image Prior
IEEE Transactions on Computational Imaging,
Journal Year:
2023,
Volume and Issue:
9, P. 1139 - 1151
Published: Jan. 1, 2023
In
recent
years,
many
deep
learning
networks
are
proposed
for
light
field
super
resolution
(LFSR).
LFSR
problem
is
essentially
ill-posed
since
unknown
detail
information
need
to
be
predicted.
Hence
require
plentiful
content
(e.g.,
shape,
color,
texture)
learned
from
sufficiently
diverse
scenarios.
However,
due
the
high
collection
cost,
existing
datasets
in
small
size
and
have
few
scenarios,
which
could
not
meet
requirement
limit
performance
of
networks.
To
solve
this
problem,
we
a
novel
framework
significantly
boost
their
performance.
Our
main
idea
introduce
valuable
single
images
into
as
prior.
Specifically,
first,
view
synthesis
method
applied
add
unreal
disparity
images,
increasing
dimensionality
hence
inconsistent
data
modalities.
Then,
design
Scenarios-Content
Introduction
Module
(SCIM)
effectively
extract
feature
synthesized
data.
Finally,
added
first
stage,
features
severely
pseudo
information.
Feature
Attention
(FAM)
discriminately
select
combine
network.
Extensive
experiments
on
six
validate
effectiveness
method,
leading
maximum
gain
0.439
dB.
can
even
SOTA
achieve
higher
Language: Английский
KULF-TT53: A Display-Specific Turntable-Based Light Field Dataset for Subjective Quality Assessment
Electronics,
Journal Year:
2023,
Volume and Issue:
12(23), P. 4868 - 4868
Published: Dec. 2, 2023
Light
field
datasets
enable
researchers
to
conduct
both
objective
and
subjective
quality
assessments,
which
are
particularly
useful
when
acquisition
equipment
or
resources
not
available.
Such
may
vary
in
terms
of
capture
technology
methodology,
content,
characteristics
(e.g.,
resolution),
the
availability
ratings.
When
contents
a
light
dataset
visualized
on
display,
display
system
matches
received
input
its
output
capabilities
through
various
processes,
such
as
interpolation.
Therefore,
one
most
straightforward
methods
create
for
specific
is
consider
visualization
parameters
during
acquisition.
In
this
paper,
we
introduce
novel
display-specific
dataset,
captured
using
DSLR
camera
turntable
rig.
The
visual
data
seven
static
scenes
were
recorded
twice
by
two
settings
angular
resolution.
While
acquired
uniformly
within
53-degree
angle,
viewing
cone
they
for,
consists
70
views
per
while
other
140.
Capturing
was
more
solution
than
downsampling,
latter
approach
could
either
degrade
make
FOV
size
inaccurate.
paper
provides
detailed
characterization
contents,
well
compressed
variations
with
codecs,
together
calculated
values
commonly-used
metrics
contents.
We
expect
that
will
be
research
community
working
compression,
processing,
assessment,
instance
perform
assessment
tests
test
new
interpolation
metrics.
future
work,
also
focus
provide
relevant
results.
This
made
free
access
community.
Language: Английский
Lightweight network with masks for light field image super-resolution based on swin attention
Multimedia Tools and Applications,
Journal Year:
2024,
Volume and Issue:
83(33), P. 79785 - 79804
Published: Feb. 29, 2024
Language: Английский
Depth-Guided Full-Focus Super-Resolution Network for Light Field Images
Published: Jan. 19, 2024
Light
field
(LF)
imaging
system
captures
the
two-dimensional
(2D)
spatial
and
2D
angular
information
of
scenes
within
a
single
exposure
time.
Due
to
this
distinctive
feature,
technique
has
been
rapidly
developed
over
past
two
decades.
However,
LF
images
suffer
from
low
resolution.
Currently,
numerous
deep
learning
(DL)-based
approaches
have
employed
address
issue.
existing
super-resolution
(SR)
networks
ignore
defocus
blur
caused
by
depth
variations,
fail
yield
high-resolution
(HR)
full-focus
directly
processing
with
information.
In
paper,
tackle
challenge,
we
propose
new
SR
method
reconstruct
HR
low-resolution
(LR)
multi-defocus
images.
To
accomplish
task,
The
degraded
dataset
is
generated
utilizing
intrinsic
as
guidance
designing
spatially-variable
(SV)
degradation
method.
designed
parts:
depth-guided
image
partitioning
process
degradation-prior-SR
network.
Experimental
results
indicated
that
our
outperforms
other
both
quantitatively
qualitatively.
Language: Английский