Name: Computer Vision: Why Now and What's Ahead ? Intel Software
Uploaded: 2019-03-24T05:19:21.000Z
Duration: 10 min 45 s
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I'm Henry Gabb, editor
of The Parallel Universe,

Intel's magazine devoted
to software innovation.

And today, I'm here
with Charlotte Dryden,

who leads a team developing
software for visual computing,

Charlotte has 20 years of
experience in semiconductors

She holds a degree in electrical
and biomedical engineering

from Vanderbilt University,
and an MBA from the University

I've done some work in
computational linguistics--

essentially, teaching
a computer how to read.

Your teaching computers how
to see more like humans.

What do you see as the
future of computer vision?

So, I work in the computer
vision software technology

many things, such as autonomous
vehicles, valet copters,

robots to move as humans
move, and see as humans see.

So I see a huge set of
opportunities there.

How do you define computer
vision, as the expert?

All the science and
technology that's needed--

which is allowing machines
to see as humans see.

rapidly more accessible to
developers of all types.

The ninja developers
who are the PhD experts,

and the maker community
and students, and even just

people who like technology
and want to try it out.

that many of the technologies
are accessible to many.

The barrier to entry seems to
have come down quite a bit.

And I agree, part of that
has to do with the software

But what else is lowering
the barrier to entry

to people who want to get
in to computer vision?

So, it used to require a big set
of servers and a lot of storage

to develop any computer
vision technology.

to require very expensive
hardware and large amounts

of time in large pools
of data to train a model

But now, the processor
speeds are faster.

Can you tell us more about what
we're doing in this segment?

So, Intel has a broad portfolio
of hardware and software

And in addition to the CPU and
the GPU for visual computing,

we now have a suite of
hardware accelerator options

and power for the right
visual computing workload.

So we have the Movidius IP
that we recently acquired,

We also have the FPGA that
we acquired from Altera

acquired Mobileye, so that we
have computer vision hardware

With that, we're in the
developer products group.

that hardware accessible to
computer vision algorithm

For example, we've developed
the computer vision SDK,

which includes a large number
of OpenCV library functions

that have been finely tuned
for all of the various hardware

And then, we have deep learning
tools to help with optimizing

And then we have a host of
tools for custom coding.

because it originated in Intel
labs almost 20 years ago.

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Computer Vision: Why Now and What's Ahead ? Intel Software

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