Stephen Lawler: Look! Up in the sky! It's Virtual Earth!

19,216 views ใƒป 2007-06-21

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Ido Dekkers ืžื‘ืงืจ: Sigal Tifferet
00:25
What I want to talk to you about today is
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ืžื” ืฉืื ื™ ืจื•ืฆื” ืœื“ื‘ืจ ืขืœื™ื• ื”ื™ื•ื
00:28
virtual worlds, digital globes, the 3-D Web, the Metaverse.
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ื”ื•ื ืขื•ืœืžื•ืช ื•ื™ืจื˜ื•ืืœื™ื™ื, ื’ืœื•ื‘ื•ืกื™ื ื“ื™ื’ื™ื˜ืœื™ื™ื, ื”ืจืฉืช ื”ืชืœืช ืžื™ืžื“ื™ืช, ื”ืžืชื-ื™ืงื•ื.
00:37
What does this all mean for us?
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ืžื” ื›ืœ ื–ื” ืื•ืžืจ ืœื ื•?
00:39
What it means is the Web is going to become an exciting place again.
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ืžื” ืฉื–ื” ืื•ืžืจ ื”ื•ื ืฉื”ืจืฉืช ื”ื•ืคื›ืช ืœื”ื™ื•ืช ืžืงื•ื ืžืจืชืง ืฉื•ื‘.
00:44
It's going to become super exciting as we transform
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ื”ื™ื ืชื”ืคืš ืœืกื•ืคืจ - ืžืจื’ืฉืช ื›ืฉื ื”ืคื•ืš ืื•ืชื”
00:47
to this highly immersive and interactive world.
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ืœืขื•ืœื ื”ืื™ื ื˜ืจืืงื˜ื™ื‘ื™ ื”ืžื•ื˜ืžืข ื”ื–ื”,
00:51
With graphics, computing power, low latencies,
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ืขื ื’ืจืคื™ืงื”, ื›ื•ื— ืžื—ืฉื•ื‘, ืขื™ื›ื•ื‘ื™ื ืงืฆืจื™ื,
00:54
these types of applications and possibilities
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ื”ืืคืœื™ืงืฆื™ื•ืช ื•ื”ืืคืฉืจื•ื™ื•ืช ื”ืืœื”
00:57
are going to stream rich data into your lives.
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ื™ื–ืจื™ืžื• ืžื™ื“ืข ืขืฉื™ืจ ืœื—ื™ื™ื ืฉืœื›ื.
01:02
So the Virtual Earth initiative, and other types of these initiatives,
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ืื– ื™ื•ื–ืžืช ื›ื“ื•ืจ ื”ืืจืฅ ื”ื•ื™ืจื˜ื•ืืœื™, ื•ื™ื•ื–ืžื•ืช ืื—ืจื•ืช ื“ื•ืžื•ืช,
01:07
are all about extending our current search metaphor.
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ื”ื ื”ื›ืœ ืื•ื“ื•ืช ื”ืจื—ื‘ื”, ืืชื ื™ื•ื“ืขื™ื, ืืช ืžื˜ืืคื•ืจืช ื”ื—ื™ืคื•ืฉ ื”ื ื•ื›ื—ื™ืช.
01:13
When you think about it, we're so constrained by browsing the Web,
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ื›ืฉื—ื•ืฉื‘ื™ื ืขืœ ื–ื”, ืื ื—ื ื• ื›ืœ ื›ืš ืžื•ื’ื‘ืœื™ื ื‘ื’ืœื™ืฉื” ื‘ืจืฉืช,
01:16
remembering URLs, saving favorites.
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ืœื–ื›ื•ืจ ืงื™ืฉื•ืจื™ื, ืœืฉืžื•ืจ ืžื•ืขื“ืคื™ื,
01:19
As we move to search, we rely on the relevance rankings,
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ื•ื›ืฉืื ื—ื ื• ืžื—ืคืฉื™ื, ืื ื—ื ื• ืžืกืชืžื›ื™ื ืขืœ ืžื“ื“ ื”ืจืœื•ื•ื ื˜ื™ื•ืช,
01:22
the Web matching, the index crawling.
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ื”ืชืืžืช ื”ืจืฉืช, ืจื•ื‘ื•ื˜ื™ ื”ืกืจื™ืงื”,
01:25
But we want to use our brain!
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ืื‘ืœ ืื ื—ื ื• ืจื•ืฆื™ื ืœื”ืฉืชืžืฉ ื‘ืžื•ื—!
01:27
We want to navigate, explore, discover information.
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ืื ื—ื ื• ืจื•ืฆื™ื ืœื ื•ื•ื˜, ืœื—ืงื•ืจ, ืœื’ืœื•ืช ืžื™ื“ืข.
01:30
In order to do that, we have to put you as a user back in the driver's seat.
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ื›ื“ื™ ืœืขืฉื•ืช ืืช ื–ื”, ืื ื—ื ื• ืฆืจื™ื›ื™ื ืœืฉื™ื ืืชื›ื ื”ืžืฉืชืžืฉื™ื ื‘ื—ื–ืจื” ื‘ืžื•ืฉื‘ ื”ื ื”ื’.
01:35
We need cooperation between you and the computing network and the computer.
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ืื ื—ื ื• ืฆืจื™ื›ื™ื ืฉื™ืชื•ืฃ ืคืขื•ืœื” ื‘ื™ื ื›ื ื•ืจืฉืช ื”ืžื—ืฉื‘ื™ื ื•ื”ืžื—ืฉื‘.
01:39
So what better way to put you back in the driver's seat
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ืื– ืื™ื–ื” ื“ืจืš ื˜ื•ื‘ื” ื™ื•ืชืจ ืœืฉื™ื ืืชื›ื ื‘ืžื•ืฉื‘ ื”ื ื”ื’
01:43
than to put you in the real world that you interact in every day?
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ืžืืฉืจ ืœืฉื™ื ืืชื›ื ื‘ืขื•ืœื ื”ืืžื™ืชื™ ืื™ืชื• ืืชื ื™ื•ืฆืจื™ื ืงืฉืจ ื›ืœ ื™ื•ื?
01:46
Why not leverage the learnings that you've been learning your entire life?
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ืœืžื” ืœื ืœืžื ืฃ ืืช ืžื” ืฉืœืžื“ืชื ื›ืœ ื”ื—ื™ื™ื?
01:50
So Virtual Earth is about starting off
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ืื– ื›ื“ื•ืจ ื”ืืจืฅ ื”ื•ื™ืจื˜ื•ืืœื™ ืืชื ื™ื•ื“ืขื™ื, ืขื•ืžื“ ืœื”ืชื—ื™ืœ,
01:53
creating the first digital representation, comprehensive, of the entire world.
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ืœื™ืฆื•ืจ ืืช ื”ื™ืฆื•ื’ ื”ื“ื™ื’ื™ื˜ืœื™ ื”ืจืืฉื•ืŸ , ื”ืžืงื™ืฃ, ืฉืœ ื”ืขื•ืœื ื›ื•ืœื•.
01:58
What we want to do is mix in all types of data.
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ืžื” ืฉืื ื—ื ื• ืจื•ืฆื™ื ืœืขืฉื•ืช ื–ื” ืœื—ื‘ืจ ืืช ื›ืœ ืกื•ื’ื™ ื”ืžื™ื“ืข.
02:01
Tag it. Attribute it. Metadata. Get the community to add local depth,
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ืœืชื™ื™ื’ ืื•ืชื, ืœืชืช ืœื”ื ืžืืคื™ื™ื ื™ื. ื ืชื•ื ื™ื ืขืœ ื”ื ืชื•ื ื™ื. ืœืชืช ืœืงื”ื™ืœื” ืœื”ื•ืกื™ืฃ ืžื™ื“ืข ืขื ืขื•ืžืง ืžืงื•ืžื™
02:06
global perspective, local knowledge.
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-- ืคืจืกืคืงื˜ื™ื‘ื” ื’ืœื•ื‘ืœื™ืช, ื™ื“ืข ืžืงื•ืžื™.
02:09
So when you think about this problem,
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ืื– ื›ืฉื—ื•ืฉื‘ื™ื ืขืœ ื”ื‘ืขื™ื” ื”ื–ืืช,
02:11
what an enormous undertaking. Where do you begin?
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ืื™ื–ื” ืžืคืขืœ ืขืฆื•ื. ืืชื ื™ื•ื“ืขื™ื, ืื™ืคื” ืžืชื—ื™ืœื™ื ?
02:15
Well, we collect data from satellites, from airplanes,
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ืื–, ืื ื—ื ื• ืื•ืกืคื™ื ืžื™ื“ืข ืžืœื•ื•ื™ื ื™ื, ืžืžื˜ื•ืกื™ื,
02:19
from ground vehicles, from people.
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ืžืจื›ื‘ื™ื ืขืœ ื”ืงืจืงืข, ืžืื ืฉื™ื.
02:22
This process is an engineering problem,
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ื”ืชื”ืœื™ืš ื”ื–ื” ื”ื•ื, ืืชื ื™ื•ื“ืขื™ื, ื–ื” ื‘ืขื™ื” ื”ื ื“ืกื™ืช,
02:27
a mechanical problem, a logistical problem, an operational problem.
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ื‘ืขื™ื” ืžื›ื ื™ืช, ื‘ืขื™ื” ืœื•ื’ื™ืกื˜ื™ืช, ื‘ืขื™ื” ืชืคืขื•ืœื™ืช.
02:31
Here is an example of our aerial camera.
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ื”ื ื” ื“ื•ื’ืžื” ืœืžืฆืœืžื” ื”ืžื•ื˜ืกืช ืฉืœื ื•.
02:33
This is panchromatic. It's actually four color cones.
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ื”ื™ื ืคืื ื›ืจื•ืžื˜ื™ืช. ื™ืฉ ืœื” ืืจื‘ืขื” ื—ืจื•ื˜ื™ ืฆื‘ืข.
02:36
In addition, it's multi-spectral.
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ื‘ื ื•ืกืฃ ื”ื™ื ืžื•ืœื˜ื™ืกืคืงื˜ืจืœื™ืช.
02:38
We collect four gigabits per second of data,
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ืื ื—ื ื• ืื•ืกืคื™ื ืžื™ื“ืข ื‘ืžืฉืงืœ 4 ื’ื™ื’ื”ื‘ื™ื˜ ืœืฉื ื™ื”,
02:42
if you can imagine that kind of data stream coming down.
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ืื ืืชื ื™ื›ื•ืœื™ื ืœืชืืจ ื›ื–ื” ื–ืจื ืฉืœ ืžื™ื“ืข ืžื’ื™ืข.
02:44
That's equivalent to a constellation of 12 satellites at highest res capacity.
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ื–ื” ืžืงื‘ื™ืœ ืœืžืขืจืš ืฉืœ 12 ืœื•ื•ื™ื ื™ื ื‘ืจื–ื•ืœื•ืฆื™ื” ื’ื‘ื•ื”ื” ื‘ื”ืกืคืง ืžืงืกื™ืžืœื™.
02:50
We fly these airplanes at 5,000 feet in the air.
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ืื ื—ื ื• ืžื˜ื™ืกื™ื ืืช ื”ืžื˜ื•ืกื™ื ื”ืืœื” ื‘ื’ื•ื‘ื” 5000 ืจื’ืœ;
02:54
You can see the camera on the front. We collect multiple viewpoints,
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ืืชื ื™ื›ื•ืœื™ื ืœืจืื•ืช ืืช ื”ืžืฆืœืžื” ื‘ื—ื–ื™ืช. ืื ื—ื ื• ืื•ืกืคื™ื ืžื ืงื•ื“ื•ืช ืžื‘ื˜ ืžืจื•ื‘ื•ืช,
02:57
vantage points, angles, textures. We bring all that data back in.
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ื ืงื•ื“ื•ืช ืขืœื™ื•ื ื•ืช, ื–ื•ื™ื•ืช, ื˜ืงืกื˜ื•ืจื•ืช. ื•ืžื—ื–ื™ืจื™ื ืืช ื›ืœ ื”ืžื™ื“ืข ื”ื–ื”.
03:03
We sit here -- you know, think about the ground vehicles, the human scale --
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ืื ื—ื ื• ื™ื•ืฉื‘ื™ื ืคื” -- ืืชื ื™ื•ื“ืขื™ื, ื”ืขื ื™ื™ืŸ ืขื ืจื›ื‘ื™ื ืขืœ ื”ืงืจืงืข, ืงื ื” ื”ืžื™ื“ื” ื”ืื ื•ืฉื™ --
03:07
what do you see in person? We need to capture that up close
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ืžื” ืจื•ืื™ื ื‘ืขืฆืžื ื•? ืื ื—ื ื• ืฆืจื™ื›ื™ื ืœืชืคื•ืก ืืช ื–ื” ืžืงืจื•ื‘
03:09
to establish that what it's like-type experience.
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ื›ื“ื™ ืœื”ืจื’ื™ืฉ ื›ืžื• ืžื” ื–ื”.
03:13
I bet many of you have seen the Apple commercials,
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ืื ื™ ืžืชืขืจื‘ ืฉืจื‘ื™ื ืจืื• ืืช ื”ืคืจืกื•ืžื•ืช ืฉืœ ืืคืœ,
03:17
kind of poking at the PC for their brilliance and simplicity.
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ืžื—ื˜ื˜ื™ื ื‘ืžื—ืฉื‘ ืœืจืื•ืช ืืช ื”ื’ืื•ื ื•ืช ื•ื”ืคืฉื˜ื•ืช ืฉืœื•.
03:23
So a little unknown secret is --
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ืื–, ืกื•ื“ ืœื ื™ื“ื•ืข ืงื˜ืŸ --
03:25
did you see the one with the guy, he's got the Web cam?
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ืจืื™ืชื ืืช ื–ืืช ืขื ื”ื‘ื—ื•ืจ, ื™ืฉ ืœื• ืืช ืžืฆืœืžืช ื”ืจืฉืช?
03:29
The poor PC guy. They're duct taping his head. They're just wrapping it on him.
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ืื™ืฉ ื”ืคื™ืกื™ ื”ืžืกื›ืŸ, ื”ื ืžื“ื‘ื™ืงื™ื ืืช ื”ืจืืฉ ืฉืœื•, ื”ื ืคืฉื•ื˜ ืžืœืคืคื™ื ืืช ื ื™ื™ืจ ื”ื“ื‘ืง ืขืœื™ื•.
03:33
Well, a little unknown secret is his brother actually works on the Virtual Earth team.
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ืื–, ืกื•ื“ ืงื˜ืŸ ื”ื•ื ืฉืื—ื™ื• ืขื•ื‘ื“ ื‘ืฆื•ื•ืช ื›ื“ื•ืจ ื”ืืจืฅ ื”ื•ื™ืจื˜ื•ืืœื™.
03:37
(Laughter). So they've got a little bit of a sibling rivalry thing going on here.
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(ืฆื—ื•ืง) ืื–, ื™ืฉ ืœื”ื ืžืจื™ื‘ืช ืื—ื™ื ืงื˜ื ื” ืฉื.
03:42
But let me tell you -- it doesn't affect his day job.
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ืื‘ืœ ืชื ื• ืœื™ ืœื”ื’ื™ื“ ืœื›ื -- ื–ื” ืœื ืžืฉืคื™ืข ืขืœ ื”ืขื‘ื•ื“ื” ืฉืœื•.
03:44
We think a lot of good can come from this technology.
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ืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืฉื”ืจื‘ื” ื˜ื•ื‘ ื™ื›ื•ืœ ืœื”ื’ื™ืข ืžื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื–ืืช.
03:47
This was after Katrina. We were the first commercial fleet of airplanes
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ื–ื” ื”ื™ื” ืื—ืจื™ ืงื˜ืจื™ื ื”. ื”ื™ื™ื ื• ืฆื™ ื”ืžื˜ื•ืกื™ื ื”ืžืกื—ืจื™ ื”ืจืืฉื•ืŸ
03:51
to be cleared into the disaster impact zone.
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ืฉื”ื•ืจืฉื” ืœื”ื›ื ืก ืœืื–ื•ืจ ื”ืืกื•ืŸ.
03:54
We flew the area. We imaged it. We sent in people. We took pictures of interiors,
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ื˜ืกื ื• ื‘ืื–ื•ืจ, ืฆื™ืœืžื ื• ืื•ืชื•, ืฉืœื—ื ื• ืคื ื™ืžื” ืื ืฉื™ื , ืœืงื—ื ื• ืชืžื•ื ื•ืช ืžื‘ืคื ื™ื,
03:59
disaster areas. We helped with the first responders, the search and rescue.
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ืื–ื•ืจื™ ืืกื•ืŸ. ืขื–ืจื ื• ืขื ื”ืžืฆื™ืœื™ื ื”ืจืืฉื•ื ื™ื, ื—ื™ืคื•ืฉ ื•ื”ืฆืœื”.
04:03
Often the first time anyone saw what happened to their house was on Virtual Earth.
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ื”ืจื‘ื” ืคืขืžื™ื ื”ืคืขื ื”ืจืืฉื•ื ื” ืฉืื ืฉื™ื ืจืื• ืžื” ืงืจื” ืœื‘ื™ืช ืฉืœื”ื ื”ื™ื” ื‘ื›ื“ื•ืจ ื”ืืจืฅ ื”ื•ื™ืจื˜ื•ืืœื™.
04:08
We made it all freely available on the Web, just to --
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ื”ืคื›ื ื• ืืช ื–ื” ืœื ื’ื™ืฉ ื—ื™ื ื ื‘ืจืฉืช, ืจืง ื›ื“ื™ -- ืืชื ื™ื•ื“ืขื™ื,
04:10
it was obviously our chance of helping out with the cause.
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ื–ื• ื”ื™ืชื” ื”ื”ื–ื“ืžื ื•ืช ืฉืœื ื• ืœืขื–ื•ืจ ืœืื ืฉื™ื ืขื ื”ืžื˜ืจื” ืฉืœื”ื.
04:14
When we think about how all this comes together,
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ื›ืฉืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืขืœ ื–ื”, ืืชื ื™ื•ื“ืขื™ื, ืื™ืš ื›ืœ ื–ื” ืžืชื—ื‘ืจ,
04:17
it's all about software, algorithms and math.
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ื–ื” ื”ื›ืœ ืชื•ื›ื ื”, ืืœื’ื•ืจื™ืชืžื™ื ื•ืžืชืžื˜ื™ืงื”.
04:21
You know, we capture this imagery but to build the 3-D models
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ืืชื ื™ื•ื“ืขื™ื, ืชืคืกื ื• ืืช ื”ืชืžื•ื ื•ืช ื”ืืœื”, ืื‘ืœ ื›ื“ื™ ืœื‘ื ื•ืช ืืช ื”ืžื•ื“ืœื™ื ื”ืชืœืช ืžื™ืžื“ื™ื™ื,
04:24
we need to do geo-positioning. We need to do geo-registering of the images.
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ื”ื™ื™ื ื• ืฆืจื™ื›ื™ื ืœืขืฉื•ืช ื’ืื•-ืžื™ืงื•ื. ืื ื—ื ื• ืฆืจื™ื›ื™ื ืœืขืฉื•ืช ื’ืื•-ืจื™ืฉื•ื ืฉืœ ื”ืชืžื•ื ื•ืช.
04:29
We have to bundle adjust them. Find tie points.
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ืื ื—ื ื• ืฆืจื™ื›ื™ื ืœื”ืชืื™ื ืื•ืชืŸ ื‘ื™ื—ื“. ืœืžืฆื•ื ืืช ื”ื ืงื•ื“ื•ืช.
04:31
Extract geometry from the images.
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ืœื”ื•ืฆื™ื ืืช ื”ื’ืื•ืžื˜ืจื™ื” ืžื”ืชืžื•ื ื•ืช.
04:34
This process is a very calculated process.
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ื–ื” ืชื”ืœื™ืš ืžืื•ื“ ืžื—ื•ืฉื‘.
04:38
In fact, it was always done manual.
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ืœืžืขืŸ ื”ืืžืช, ื–ื” ืชืžื™ื“ ื ืขืฉื” ื™ื“ื ื™ืช.
04:39
Hollywood would spend millions of dollars to do a small urban corridor
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ื”ื•ืœื™ื•ื•ื“ ื”ื™ื• ืžื•ืฆื™ืื™ื ืžื™ืœื™ื•ื ื™ ื“ื•ืœืจื™ื ืขืœ ืžืกื“ืจื•ืŸ ืื•ืจื‘ื ื™
04:43
for a movie because they'd have to do it manually.
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ืœืกืจื˜ ืžืคื ื™ ืฉื”ื ื”ื™ื• ืฆืจื™ื›ื™ื ืœืขืฉื•ืช ืืช ื–ื” ื™ื“ื ื™ืช.
04:46
They'd drive the streets with lasers called LIDAR.
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ื”ื ื ื”ื’ื• ื‘ืจื—ื•ื‘ื•ืช ืขื ืœื™ื™ื–ืจ ืฉื ืงืจื LIDAR.
04:48
They'd collected information with photos. They'd manually build each building.
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ื”ื ืืกืคื• ืžื™ื“ืข ืขื ืชืžื•ื ื•ืช; ื”ื ื”ื™ื• ื‘ื•ื ื™ื ื™ื“ื ื™ืช ื›ืœ ื‘ื ื™ื™ืŸ.
04:52
We do this all through software, algorithms and math --
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ืื ื—ื ื• ืขื•ืฉื™ื ืืช ื–ื” ื‘ืชื•ื›ื ื”, ืืœื’ื•ืจื™ืชืžื™ื ื•ืžืชืžื˜ื™ืงื”,
04:54
a highly automated pipeline creating these cities.
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ืชื”ืœื™ืš ืžืื•ื“ ืื•ื˜ื•ืžื˜ื™ ืฉื™ื•ืฆืจ ืืช ื”ืขืจื™ื ื”ืืœื”.
04:57
We took a decimal point off what it cost to build these cities,
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ื”ื•ืจื“ื ื• ื ืงื•ื“ื” ืขืฉืจื•ื ื™ืช ืžืžื” ืฉืขืœื” ืœื‘ื ื•ืช ืืช ื”ืขืจื™ื ื”ืืœื”,
05:00
and that's how we're going to be able to scale this out and make this reality a dream.
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ื•ื›ื›ื” ื ื•ื›ืœ ืœื”ื’ื“ื™ืœ ืืช ื–ื” ื•ืœื”ืคื•ืš ืืช ื”ื—ืœื•ื ืœืžืฆื™ืื•ืช.
05:04
We think about the user interface.
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ืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืขืœ ืžืžืฉืง ื”ืžืฉืชืžืฉ.
05:06
What does it mean to look at it from multiple perspectives?
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ืžื” ื–ื” ืื•ืžืจ ืœื”ื‘ื™ื˜ ื‘ื–ื” ืžืคืจืกืคืงื˜ื™ื‘ื•ืช ืžืจื•ื‘ื•ืช?
05:09
An ortho-view, a nadir-view. How do you keep the precision of the fidelity of the imagery
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ืžื‘ื˜ ื ื™ืฆื‘, ืžื‘ื˜ ื ื“ื™ืจ. ืื™ืš ืฉื•ืžืจื™ื ืขืœ ื”ื“ื™ื•ืง ืฉืœ ื—ื“ื•ืช ื”ืชืžื•ื ื”
05:14
while maintaining the fluidity of the model?
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ื•ืขื“ื™ื™ืŸ ืฉื•ืžืจื™ื ืขืœ ื”ื–ืจื™ืžื” ืฉืœ ื”ืžื•ื“ืœ?
05:18
I'll wrap up by showing you the --
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ืื ื™ ืืกื™ื™ื ื‘ืœื”ืจืื•ืช ืœื›ื ืืช --
05:20
this is a brand-new peek I haven't really shown into the lab area of Virtual Earth.
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ื–ื• ื”ืฆืฆื” ื—ื“ืฉื” ืฉืขื“ื™ื™ืŸ ืœื ื”ืจืืชื™ ืœืžืขื‘ื“ื” ืฉืœ ื›ื“ื•ืจ ื”ืืจืฅ ื”ื•ื™ืจื˜ื•ืืœื™.
05:24
What we're doing is -- people like this a lot,
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ืžื” ืฉืื ื—ื ื• ืขื•ืฉื™ื ื–ื” -- ืื ืฉื™ื ื›ืืœื” ื”ืจื‘ื” --
05:27
this bird's eye imagery we work with. It's this high resolution data.
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ืชืžื•ื ื” ืžืžื‘ื˜ ื”ืฆื™ืคื•ืจ ืฉืื ื—ื ื• ืขื•ื‘ื“ื™ื ืื™ืชืŸ. ื–ื” ืžื™ื“ืข ื‘ืจื–ื•ืœื•ืฆื™ื” ื’ื‘ื•ื”ื”.
05:30
But what we've found is they like the fluidity of the 3-D model.
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ืื‘ืœ ืžื” ืฉืžืฆืื ื• ื–ื” ืฉื”ื ืื•ื”ื‘ื™ื ืืช ื”ื–ืจื™ืžื” ืฉืœ ื”ืžื•ื“ืœ ื”ืชืœืช ืžื™ืžื“ื™.
05:34
A child can navigate with an Xbox controller or a game controller.
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ื™ืœื“ ื™ื›ื•ืœ ืœื ื•ื•ื˜ ืขื ื‘ืงืจ ื”XBOX, ืื• ื‘ืงืจ ืžืฉื—ืง.
05:38
So here what we're trying to do is we bring the picture and project it into the 3-D model space.
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ืื– ื›ืืŸ ืžื” ืฉืื ื—ื ื• ืžื ืกื™ื ืœืขืฉื•ืช ื–ื” ืœื”ื‘ื™ื ืืช ื”ืชืžื•ื ื” ื•ื”ืคืจื•ื™ื™ืงื˜ ืœืžืจื—ื‘ ื”ืžื•ื“ืœ ื”ืชืœืช ืžื™ืžื“ื™.
05:43
You can see all types of resolution. From here, I can slowly pan the image over.
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ืืชื ื™ื›ื•ืœื™ื ืœืจืื•ืช ืžื’ื•ื•ืŸ ืจื–ื•ืœื•ืฆื™ื•ืช. ืžื›ืืŸ, ืื ื™ ื™ื›ื•ืœ ืœื”ื–ื™ื– ืืช ื”ืชืžื•ื ื”.
05:49
I can get the next image. I can blend and transition.
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ืื ื™ ื™ื›ื•ืœ ืœืงื‘ืœ ืืช ื”ืชืžื•ื ื” ื”ื‘ืื”. ืื ื™ ื™ื›ื•ืœ ืœืžื–ื’ ื•ืœื”ื–ื™ื–.
05:52
By doing this I don't lose the original detail. In fact, I might be recording history.
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ื•ื‘ื–ื” ืื ื™ ืœื ืžืื‘ื“ ืืช ื”ืคืจื˜ื™ื ื”ืžืงื•ืจื™ื™ื. ืœืžืขืฉื”, ืื ื™ ื™ื›ื•ืœ ืœื”ืงืœื™ื˜ ื”ื™ืกื˜ื•ืจื™ื”.
05:57
The freshness, the capacity. I can turn this image.
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ื”ื˜ืจื™ื•ืช, ื”ืงื™ื‘ื•ืœืช. ืื ื™ ื™ื›ื•ืœ ืœืกื•ื‘ื‘ ืืช ื”ืชืžื•ื ื”.
06:00
I can look at it from multiple viewpoints and angles.
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ืื ื™ ื™ื›ื•ืœ ืœื”ื‘ื™ื˜ ื‘ื” ืžื›ื™ื•ื•ื ื™ื ื•ื–ื•ื•ื™ื•ืช ืฉื•ื ื•ืช.
06:03
What we're trying to do is build a virtual world.
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ืžื” ืฉืื ื—ื ื• ืžื ืกื™ื ืœืขืฉื•ืช ื–ื” ืœื‘ื ื•ืช ืขื•ืœื ื•ื™ืจื˜ื•ืืœื™.
06:06
We hope that we can make computing a user model you're familiar with,
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ืื ื—ื ื• ืžืงื•ื•ื™ื ืฉื ื•ื›ืœ ืœืขืฉื•ืช ืืช ื”ืžื—ืฉื•ื‘ ืœืžื•ื“ืœ ืžืฉืชืžืฉ ืฉืืชื ืžื›ื™ืจื™ื,
06:11
and really derive insights from you, from all different directions.
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ื•ื‘ืืžืช ืœืงื‘ืœ ืชื•ื‘ื ื•ืช ืžื›ื, ืžื›ืœ ืžื™ื ื™ ื›ื™ื•ื•ื ื™ื ืฉื•ื ื™ื.
06:15
I thank you very much for your time.
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ืื ื™ ืžื•ื“ื” ืœื›ื ืžืื•ื“ ืขืœ ื”ื–ืžืŸ ืฉื ืชืชื ืœื™.
06:17
(Applause)
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(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

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