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Embedded Vision has been the buzz word
in the imaging industry for quite a while.
Unquestionably, there is a huge potential
for Embedded Vision to change industries’
business models, to take vision to the
next level, and to allows devices to see
and think in all industrial and consumer
markets. But how is this different than
the classic vision technology? How can
all industries, virtually all devices and
every_thing, leverage and benefit from
the embedded Vision of Things?
The Internet of Things (IoT) creates the
swarm intelligence of holistic systems by
connecting all devices among one another
to interact accordingly. Embedded Vision
technologies provide the eyes and brain
power (AI) for autonomous decision
making without any human interaction
to empower the Vision of Things (VoT)
to act intelligently within the Internet of
Things.
What differentiates
Embedded Vision from
Classic Vision?
Regular vision systems are mainly built
human interactions within the imaging
pipeline and allows machines to make
their own decisions by capturing,
analyzing and interpreting the data
all-in-one.
From a developer’s standpoint,
classic vision systems were mostly
made to support numerous verticals
with multitude of possible tasks to
be programmed. This broad variety
is the main reason for the large
processing
space
requirements
needed off-board. Embedded Vision
tends to be more laser-focused in
its applications, it is designed for a
specific task. This “purpose-build”
approach opens new possibilities and
frees processing space to be used for
neural intelligence algorithms. From
the vision manufacturer perspective,
he does not have to provide a one-
fits-all product and cover all possible
use cases, but can be specializes and
focus his development on the “how”
of a specific system which will be
customized later by the OEM developer
to satisfy his unique requirements.
Re-Defining Embedded Vision
SMART IMAGING FOR THE VISION OF THINGS
Darren Bessette, FRAMOS
with a camera that is connected to a
host PC with a known data interface.
The system is mostly separated into the
machine that run and the controlling
process that do the inspection. The
processing of the video stream and
images are mostly outsourced and
often needs user interaction for
validation and/or decision making. A
surveillance application may recognizes
people, but a security officer needs to
validate any abnormal occurrence to
determine if it is a threat that needs an
immediate response. In comparison,
a security based Embedded Vision
application would be able to assess
the thread, determine that the threat
is a person of interest and alert the
authorities to react accordingly. In
this case, the vision technology inside
of a device, a complete system with
intelligent on-board processing, is able
to provide an appropriate response
without any human operator oversight.
Embedded Vision is not only part of the
device, it is its smart eye. In its entirety
Embedded Vision minimizes or removes
64 l New-Tech Magazine Europe