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

19,189 views ・ 2007-06-21

TED


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翻译人员: Chunlei Chang 校对人员: dahong zhang
00:25
What I want to talk to you about today is
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我今天想要谈的是
00:28
virtual worlds, digital globes, the 3-D Web, the Metaverse.
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虚拟世界,数字地球,三维网络和网络虚拟实境.
00:37
What does this all mean for us?
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这些东西对于我们意味着什么?
00:39
What it means is the Web is going to become an exciting place again.
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这意味着网络又将变成一个令人激动的地方.
00:44
It's going to become super exciting as we transform
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让我们非常兴奋的是随着我们加入这个
00:47
to this highly immersive and interactive world.
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身临其境和高度交互的世界,
00:51
With graphics, computing power, low latencies,
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这个拥有各种图形,高计算能力和低延迟的世界.
00:54
these types of applications and possibilities
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这类的应用程序和它创造的可能性
00:57
are going to stream rich data into your lives.
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将把丰富的数据流带进你的生活.
01:02
So the Virtual Earth initiative, and other types of these initiatives,
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所以,虚拟地球的出现, 或者其它这种类型的程序的出现,
01:07
are all about extending our current search metaphor.
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都是关于扩展我们当前的搜索方法的.
01:13
When you think about it, we're so constrained by browsing the Web,
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思考一下,我们在浏览网络时总是被限制着.
01:16
remembering URLs, saving favorites.
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记网址,保存到"我的最爱".
01:19
As we move to search, we rely on the relevance rankings,
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当搜索出现后,我们依赖于
01:22
the Web matching, the index crawling.
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相关性排名,网络匹配和索引检索.
01:25
But we want to use our brain!
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但我们要用我们的大脑!
01:27
We want to navigate, explore, discover information.
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我们要自己去航行,探索和发现信息.
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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为了这样做,我们必须把用户放回驾驶员的座位上.
01:35
We need cooperation between you and the computing network and the computer.
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我们需要你与网络和计算机之间的合作.
01:39
So what better way to put you back in the driver's seat
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有什么更好的方法比把你放在驾驶员的座位上
01:43
than to put you in the real world that you interact in every day?
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把你放在每天都接触的真实世界里还要好呢?
01:46
Why not leverage the learnings that you've been learning your entire life?
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为什么不去利用你在生活中学过的知识呢?
01:50
So Virtual Earth is about starting off
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所以,虚拟地球是关于
01:53
creating the first digital representation, comprehensive, of the entire world.
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创造第一个数字表达的,综合的世界.
01:58
What we want to do is mix in all types of data.
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我们要做的是混合所有类型的数据.
02:01
Tag it. Attribute it. Metadata. Get the community to add local depth,
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给它做上标记,加上属性和元数据. 理解本地社区并加上本地内容
02:06
global perspective, local knowledge.
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-- 全球的视角, 本地的知识.
02:09
So when you think about this problem,
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那么,当你思考这个问题的时候,
02:11
what an enormous undertaking. Where do you begin?
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这是多么大的一个任务. 你想, 从哪儿着手做呢?
02:15
Well, we collect data from satellites, from airplanes,
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我们通过卫星,飞机
02:19
from ground vehicles, from people.
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地面车辆和人来采集数据.
02:22
This process is an engineering problem,
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这是我们的方法, 你知道, 这是一个工程问题.
02:27
a mechanical problem, a logistical problem, an operational problem.
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一个机械问题, 一个逻辑问题和一个运营问题.
02:31
Here is an example of our aerial camera.
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这是航空摄像机的一个例子.
02:33
This is panchromatic. It's actually four color cones.
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这是一个全色相机. 它其实有四个彩色锥体.
02:36
In addition, it's multi-spectral.
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另外, 它是多光谱的.
02:38
We collect four gigabits per second of data,
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我们每秒种可以采集到4GB的数据,
02:42
if you can imagine that kind of data stream coming down.
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如果你能想像这种数据流传输下来,
02:44
That's equivalent to a constellation of 12 satellites at highest res capacity.
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那相当于一个12个卫星的星座用最高清分辨率拍摄的数据量.
02:50
We fly these airplanes at 5,000 feet in the air.
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我们驾驶这些飞机到5000英尺的高空;
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You can see the camera on the front. We collect multiple viewpoints,
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你可以看到前置摄像机. 我们选择
02:57
vantage points, angles, textures. We bring all that data back in.
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多视点, 有利位置, 角度, 结构. 我们把数据带回来.
03:03
We sit here -- you know, think about the ground vehicles, the human scale --
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我们坐在这儿 -- 你知道, 关于地面车辆和人的比例.
03:07
what do you see in person? We need to capture that up close
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你自己看到了什么? 我们需要近距离捕捉他们来建立一种
03:09
to establish that what it's like-type experience.
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逼真的体验.
03:13
I bet many of you have seen the Apple commercials,
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我想你们大多数人都看过Apple商业展广告,
03:17
kind of poking at the PC for their brilliance and simplicity.
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有点嘲笑PC电脑来表现出他们的简洁和光辉.
03:23
So a little unknown secret is --
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那么, 一个不为人知秘密是 --
03:25
did you see the one with the guy, he's got the Web cam?
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你有没有看到一个带着网络摄像机的家伙?
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The poor PC guy. They're duct taping his head. They're just wrapping it on him.
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这个可怜的PC男孩, 头上带着管子, 他们给他包装成那样儿.
03:33
Well, a little unknown secret is his brother actually works on the Virtual Earth team.
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好, 一个不为人知的秘密是他的哥哥,其实在虚拟地球研发团队工作.
03:37
(Laughter). So they've got a little bit of a sibling rivalry thing going on here.
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(笑声). 那么, 那里表达一些兄弟之间对抗的东西.
03:42
But let me tell you -- it doesn't affect his day job.
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但我告诉你 -- 这没有影响他每天的工作.
03:44
We think a lot of good can come from this technology.
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我们想像这个科技带来很多的好处.
03:47
This was after Katrina. We were the first commercial fleet of airplanes
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这是在Katrina飓风之后. 我们曾是灾难区域里的
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to be cleared into the disaster impact zone.
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第一个商业飞行队.
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We flew the area. We imaged it. We sent in people. We took pictures of interiors,
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我们飞到那个区域,拍下照片, 发给大家. 我们在灾区深入拍摄图片.
03:59
disaster areas. We helped with the first responders, the search and rescue.
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我们帮助应急救生员, 搜索和营救.
04:03
Often the first time anyone saw what happened to their house was on Virtual Earth.
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常常是人们是首先通过虚拟地球看到他们房屋的情况.
04:08
We made it all freely available on the Web, just to --
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我们通过网络把这些免费提供给所有人, 是为了 -- 你知道,
04:10
it was obviously our chance of helping out with the cause.
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这明显是我们为灾区人们提供帮助的机会.
04:14
When we think about how all this comes together,
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当我们思考它时, 你知道, 这些东西如何组合到一起的.
04:17
it's all about software, algorithms and math.
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全是关于软件, 算法和数学.
04:21
You know, we capture this imagery but to build the 3-D models
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你知道, 我们捕捉图像,但是为了构建三维模型,
04:24
we need to do geo-positioning. We need to do geo-registering of the images.
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我们需要做地理定位. 我们需要做图片的地理标记.
04:29
We have to bundle adjust them. Find tie points.
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我们必须收集调整他们. 找到联结点.
04:31
Extract geometry from the images.
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完全是图像的几何学.
04:34
This process is a very calculated process.
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这个过程完全是个计算的过程.
04:38
In fact, it was always done manual.
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实际上, 几乎都是通过人工去计算的.
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Hollywood would spend millions of dollars to do a small urban corridor
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好莱坞愿意花上百万美金去计算电影中的一个小市区走廊
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for a movie because they'd have to do it manually.
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因为他们必须用手工计算.
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They'd drive the streets with lasers called LIDAR.
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他们用激光扫描探测技术在街道上驾驶.
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They'd collected information with photos. They'd manually build each building.
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他们收集图片信息; 他们手工建造每个大楼.
04:52
We do this all through software, algorithms and math --
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我们做这些完全通过软件, 算法和数学.
04:54
a highly automated pipeline creating these cities.
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一个高度自动化的流水线来建造这些城市.
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We took a decimal point off what it cost to build these cities,
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我们在建造这些城市的费用上加一个小数点.
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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这就是我们为什么能把规模做大并且将现实转化成虚拟.
05:04
We think about the user interface.
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我们考虑用户界面.
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What does it mean to look at it from multiple perspectives?
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采用多视角意味着什么?
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An ortho-view, a nadir-view. How do you keep the precision of the fidelity of the imagery
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一个鸟瞰视角, 一个垂直俯视. 你要如何保持图像的精度的同时
05:14
while maintaining the fluidity of the model?
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保持模型的流畅性?
05:18
I'll wrap up by showing you the --
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我会给你展示 --
05:20
this is a brand-new peek I haven't really shown into the lab area of Virtual Earth.
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这是个全新的俯视图我还没有放入虚拟地球的实验室区域.
05:24
What we're doing is -- people like this a lot,
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我们要做的是 -- 人们喜欢这个
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this bird's eye imagery we work with. It's this high resolution data.
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我们要做的鸟瞰图. 是高解析度的数据.
05:30
But what we've found is they like the fluidity of the 3-D model.
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但我们发现他们像三维模型的流畅度.
05:34
A child can navigate with an Xbox controller or a game controller.
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孩子们可以使用Xbox或游戏机去探索.
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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这里,我们正尝试将图片映射到三维模型空间中.
05:43
You can see all types of resolution. From here, I can slowly pan the image over.
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你可以看到所有的分辨率. 从这里,我可以慢慢平移图像.
05:49
I can get the next image. I can blend and transition.
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我可以看到下一张图片, 我可以结合和过渡.
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By doing this I don't lose the original detail. In fact, I might be recording history.
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做这些操作时,我不会损失任何细节. 实际上,我有可能在记录历史.
05:57
The freshness, the capacity. I can turn this image.
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新奇,能力. 我可以转动这个图像.
06:00
I can look at it from multiple viewpoints and angles.
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我可以查看多视点和多角度.
06:03
What we're trying to do is build a virtual world.
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我们正在做的是, 打造一个虚拟世界.
06:06
We hope that we can make computing a user model you're familiar with,
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我们希望可以计算出一个你熟悉的用户模型.
06:11
and really derive insights from you, from all different directions.
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可以从你的角度,从所有不同的角度浏览.
06:15
I thank you very much for your time.
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谢谢.
06:17
(Applause)
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(掌声)
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