Abe Davis: New video technology that reveals an object's hidden properties

204,153 views ・ 2015-05-05

TED


請雙擊下方英文字幕播放視頻。

譯者: Tian Meng 審譯者: Coco Shen
00:13
Most of us think of motion as a very visual thing.
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絕大部分的人認為 「動作」是非常視覺的。
00:17
If I walk across this stage or gesture with my hands while I speak,
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如果我走過這個舞台, 或在說話的時候使用手勢,
00:22
that motion is something that you can see.
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這些動作都是你可以看見的。
00:26
But there's a world of important motion that's too subtle for the human eye,
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但有一些細微的重要動作, 是人類的眼睛無法看見的。
00:31
and over the past few years,
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而在過去的幾年中,
00:33
we've started to find that cameras
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我們發現鏡頭,
00:35
can often see this motion even when humans can't.
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能夠看到這些人類所看不見的動作。
00:40
So let me show you what I mean.
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所以讓我來帶大家了解一下,
00:42
On the left here, you see video of a person's wrist,
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在左邊,你可以看到一個人手腕的影片;
00:46
and on the right, you see video of a sleeping infant,
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在右邊,你可以看到一個睡著嬰兒的影片。
00:49
but if I didn't tell you that these were videos,
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但是如果我沒有告訴你這是影片的話,
00:52
you might assume that you were looking at two regular images,
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你有可能會認為 你只是在看兩張非常普通的圖片。
因為在這兩個情況之下,
00:56
because in both cases,
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這些影片看起來只是完全靜止的。
00:58
these videos appear to be almost completely still.
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01:02
But there's actually a lot of subtle motion going on here,
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事實上這裏發生著許多細微的動作。
01:06
and if you were to touch the wrist on the left,
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如果你觸碰左邊手腕的話,
01:08
you would feel a pulse,
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你會感覺到脈搏。
01:10
and if you were to hold the infant on the right,
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如果你抱起這個右邊嬰兒的話,
01:12
you would feel the rise and fall of her chest
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你會感覺到她的胸部上下起伏,
01:15
as she took each breath.
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當她正在呼吸的時候。
01:17
And these motions carry a lot of significance,
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這些動作十分重要,
01:21
but they're usually too subtle for us to see,
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但對我們來說太細微 以至於我們看不到。
01:24
so instead, we have to observe them
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所以我們要用
01:26
through direct contact, through touch.
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直接的觸碰去感知它們。
01:30
But a few years ago,
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但是,幾年前,
01:32
my colleagues at MIT developed what they call a motion microscope,
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我麻省理工的同事 研究出了動作顯微鏡。
01:36
which is software that finds these subtle motions in video
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這軟體可用來尋找影片中的細微動作,
01:41
and amplifies them so that they become large enough for us to see.
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然後將它們放大使得我們可以看到。
01:45
And so, if we use their software on the left video,
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所以說,如果我們在左邊的影片上 使用那個軟體,
01:48
it lets us see the pulse in this wrist,
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它能讓我們看到腕部的脈搏。
01:52
and if we were to count that pulse,
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而且如果我們數一數脈搏的話,
01:53
we could even figure out this person's heart rate.
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我們甚至可以得出這個人的心率。
01:57
And if we used the same software on the right video,
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如果我們在右邊的影片上用同一軟體的話,
02:00
it lets us see each breath that this infant takes,
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它可以讓我們看到嬰兒的每一個呼吸。
02:03
and we can use this as a contact-free way to monitor her breathing.
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我們可以將這個軟體視為 不用接觸就能觀察嬰兒呼吸的探測器。
02:08
And so this technology is really powerful because it takes these phenomena
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所以這種科技非常強大, 它記錄的現象
是原本我們得觸摸才能感受到的現象,
02:14
that we normally have to experience through touch
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02:16
and it lets us capture them visually and non-invasively.
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而且它可以讓我們可視地、無創地觀察他們。
02:21
So a couple years ago, I started working with the folks that created that software,
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所以數年以前,我開始 和這些開發軟體的人一起工作,
02:25
and we decided to pursue a crazy idea.
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然後我們決定去追尋一個瘋狂的主意。
02:28
We thought, it's cool that we can use software
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我們認為用這個軟體發現細小的動作
02:31
to visualize tiny motions like this,
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是很酷炫的,
02:34
and you can almost think of it as a way to extend our sense of touch.
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而且可以將它視為我們觸覺的延伸。
02:39
But what if we could do the same thing with our ability to hear?
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但是如果我們可以 做出擴展我們聽覺的軟體呢?
02:44
What if we could use video to capture the vibrations of sound,
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如果我們可以通過影片 從而獲得聲音的振動,
02:49
which are just another kind of motion,
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振動是另外一種動作,
02:52
and turn everything that we see into a microphone?
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然後將我們看到的所有東西 轉化為聲音進入麥克風呢?
02:56
Now, this is a bit of a strange idea,
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這是一個有點奇怪的主意,
02:58
so let me try to put it in perspective for you.
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所以讓我將它變得更加易懂一些。
03:01
Traditional microphones work by converting the motion
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傳統的麥克風通過將內部隔膜的振動
03:05
of an internal diaphragm into an electrical signal,
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轉換為電信號,
03:08
and that diaphragm is designed to move readily with sound
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設計讓隔膜隨著聲音方便移動。
03:12
so that its motion can be recorded and interpreted as audio.
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它的振動可以被記錄和轉換成聲音。
03:17
But sound causes all objects to vibrate.
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但是聲音可以使任何物體產生振動。
03:21
Those vibrations are just usually too subtle and too fast for us to see.
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那些振動與我們來說太小太快, 以至於我們不能看不見。
03:26
So what if we record them with a high-speed camera
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要是我們用高速錄影機記錄下振動,
03:30
and then use software to extract tiny motions
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然後用軟體從高速錄影機的影片中
分離出細微的動作,
03:34
from our high-speed video,
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03:36
and analyze those motions to figure out what sounds created them?
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然後分析那些動作 並且搞清楚是什麼聲音創造了振動呢?
03:41
This would let us turn visible objects into visual microphones from a distance.
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這樣我們可以在一定距離內 將可視物體轉換到可視話筒中。
03:49
And so we tried this out,
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然後我們進行了實驗。
03:51
and here's one of our experiments,
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這裏可以看到我們的實驗。
03:53
where we took this potted plant that you see on the right
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在右邊我們放置了一盆盆栽,
03:56
and we filmed it with a high-speed camera
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然後我們用高速錄影機記錄了下來。
03:58
while a nearby loudspeaker played this sound.
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同事在邊上用擴音器發出這個聲音。
04:02
(Music: "Mary Had a Little Lamb")
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(音樂:“瑪麗有隻小綿羊”)
04:11
And so here's the video that we recorded,
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然後下面是我們記錄下的聲音。
04:14
and we recorded it at thousands of frames per second,
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我們每秒鐘記錄下上千次畫面,
04:18
but even if you look very closely,
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但是就算你再仔細地看,
04:20
all you'll see are some leaves
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你只會看到一些好看的樹葉,
04:22
that are pretty much just sitting there doing nothing,
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就只是靜止在那什麼也不做。
04:25
because our sound only moved those leaves by about a micrometer.
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那是因為我們的聲音 只移動了樹葉大約一微米的距離,
04:31
That's one ten-thousandth of a centimeter,
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那個距離大概是萬分之一釐米,
04:35
which spans somewhere between a hundredth and a thousandth
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在千分之一和百分之一之間,
04:39
of a pixel in this image.
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只是這一個圖像的像素點。
04:41
So you can squint all you want,
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所以你可以盡量瞇著眼睛看,
04:44
but motion that small is pretty much perceptually invisible.
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但是細小的動作是不容易被感知到的。
04:49
But it turns out that something can be perceptually invisible
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但結果卻是一些不容易被看到的物體,
04:53
and still be numerically significant,
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在數字上仍然非常重要。
04:56
because with the right algorithms,
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因為當使用了正確的演算法之後,
04:58
we can take this silent, seemingly still video
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我們可以獲取這段看起來靜止無聲的影片,
05:02
and we can recover this sound.
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然後還原出聲音。
05:04
(Music: "Mary Had a Little Lamb")
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(音樂:“瑪麗有隻小綿羊”)
05:12
(Applause)
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(掌聲)
05:22
So how is this possible?
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這是為什麼呢?
05:23
How can we get so much information out of so little motion?
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我們是如何在這細小的動作中 得到如此多訊息的呢?
05:28
Well, let's say that those leaves move by just a single micrometer,
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那麼讓我們假設這些樹葉 只是移動了一點點距離,
05:33
and let's say that that shifts our image by just a thousandth of a pixel.
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再者樹葉只是移動了 千分之一個像素的距離。
05:39
That may not seem like much,
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那看起來並不多,
05:41
but a single frame of video
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但是一個單一幀率的影片,
05:43
may have hundreds of thousands of pixels in it,
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可能有不計其數的像素。
05:47
and so if we combine all of the tiny motions that we see
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所以如果我們將這些細小的動作
05:50
from across that entire image,
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從整個畫面中截取出來的話,可以看到
05:52
then suddenly a thousandth of a pixel
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一個像素的千分之一
05:55
can start to add up to something pretty significant.
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可以累計變得十分重要。
05:58
On a personal note, we were pretty psyched when we figured this out.
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就我個人來說, 我們研究出來時高興得都要瘋了。
06:02
(Laughter)
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(笑聲)
06:04
But even with the right algorithm,
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但是就算擁有正確的算法,
06:08
we were still missing a pretty important piece of the puzzle.
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我們仍然會丟失整個拼圖中最重要的部分。
06:11
You see, there are a lot of factors that affect when and how well
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你們知道有許多的因素
會對這個技術正常工作造成影響。
06:15
this technique will work.
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06:17
There's the object and how far away it is;
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這些因素包括,物體離得有多少遠、
06:20
there's the camera and the lens that you use;
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拍攝的時候使用的鏡頭、
06:22
how much light is shining on the object and how loud your sound is.
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有多少光照在物體上,還有放出的聲音多響。
06:27
And even with the right algorithm,
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而且就算擁有正確的算法,
06:31
we had to be very careful with our early experiments,
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我們在早期的試驗中必須十分小心。
06:34
because if we got any of these factors wrong,
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如果說我們弄錯了其中任何一個細節,
06:37
there was no way to tell what the problem was.
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我們沒有辦法找出問題所在,
06:39
We would just get noise back.
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只會得到一段噪音。
06:42
And so a lot of our early experiments looked like this.
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所以我們早期的研究是像這樣的。
06:45
And so here I am,
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這就是我。
06:47
and on the bottom left, you can kind of see our high-speed camera,
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在畫面的左下角可以看到我們的高速錄影機,
06:51
which is pointed at a bag of chips,
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它正對著一包洋芋片,
06:53
and the whole thing is lit by these bright lamps.
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所有的事物被一盞燈所照亮。
06:56
And like I said, we had to be very careful in these early experiments,
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就像我說的,我們需要格外小心。
07:01
so this is how it went down.
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這就是這個試驗如何進行的。
07:03
(Video) Abe Davis: Three, two, one, go.
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(影片)亞伯戴維斯:三二一開始。
07:07
Mary had a little lamb! Little lamb! Little lamb!
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瑪麗有隻小綿羊 小綿羊!小綿羊!
07:12
(Laughter)
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(笑聲)
07:17
AD: So this experiment looks completely ridiculous.
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亞伯戴維斯:所以這個實驗看起來十分可笑。
07:20
(Laughter)
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(笑聲)
07:21
I mean, I'm screaming at a bag of chips --
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我對著一袋洋芋片尖叫。
07:24
(Laughter) --
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(笑聲)
07:25
and we're blasting it with so much light,
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我們在充足的光照下對著它大叫,
07:27
we literally melted the first bag we tried this on. (Laughter)
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我們確實將第一個實驗的洋芋融化了。(笑聲)
07:32
But ridiculous as this experiment looks,
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儘管看上去很可笑,
07:35
it was actually really important,
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這確實是十分重要,
07:37
because we were able to recover this sound.
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因為我們可以復原這個聲音。
07:40
(Audio) Mary had a little lamb! Little lamb! Little lamb!
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(聲音)瑪麗有隻小綿羊,小綿羊!小綿羊!
07:45
(Applause)
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(掌聲)
07:49
AD: And this was really significant,
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這是十分重要的。
07:51
because it was the first time we recovered intelligible human speech
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因為這是第一次 我們從一個物體靜止的影像中,
07:55
from silent video of an object.
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復原出了清楚的人聲。
07:57
And so it gave us this point of reference,
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所以這給了我們一個參考,
08:00
and gradually we could start to modify the experiment,
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並且可以逐漸去修改這個實驗。
08:04
using different objects or moving the object further away,
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用不同的物體或者把物體移到更遠的地方,
08:07
using less light or quieter sounds.
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或者使用少量的光和更加輕的聲音。
08:11
And we analyzed all of these experiments
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我們分析了實驗,
08:14
until we really understood the limits of our technique,
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直到我們弄清楚我們技術的侷限性在哪,
08:18
because once we understood those limits,
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因為只要我們明白它們的極限,
08:20
we could figure out how to push them.
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就可以知道如何去推動它們。
08:22
And that led to experiments like this one,
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我們的實驗就可能變成這一個,
08:25
where again, I'm going to speak to a bag of chips,
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我在同一個地方 再一次向一包洋芋片說話,
08:28
but this time we've moved our camera about 15 feet away,
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但是這一次我們把攝影機往後移動了15英尺,
08:33
outside, behind a soundproof window,
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放置在隔音玻璃後面,
08:36
and the whole thing is lit by only natural sunlight.
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所有的東西僅僅是被太陽光所照亮。
08:40
And so here's the video that we captured.
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這是我們拍攝到的影片。
08:44
And this is what things sounded like from inside, next to the bag of chips.
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聽起來這個聲音是從洋芋片內部發出來的。
08:49
(Audio) Mary had a little lamb whose fleece was white as snow,
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(聲音)瑪麗有隻小綿羊, 牠的毛白得像雪一樣。
08:54
and everywhere that Mary went, that lamb was sure to go.
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並且瑪麗走到哪裏, 小綿羊就跟到哪裏。
08:59
AD: And here's what we were able to recover from our silent video
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這是我們能夠通過在玻璃外面捕捉的
09:03
captured outside behind that window.
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靜止影像中還原出來的。
09:06
(Audio) Mary had a little lamb whose fleece was white as snow,
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(聲音)瑪麗有隻小綿羊, 牠的毛白得像雪一樣。
09:10
and everywhere that Mary went, that lamb was sure to go.
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並且瑪麗走到哪裏, 小綿羊就跟到哪裏。
09:15
(Applause)
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(掌聲)
09:22
AD: And there are other ways that we can push these limits as well.
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還有其他辦法去推動這些限制,
09:25
So here's a quieter experiment
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所以下面是一個更安靜的實驗。
09:27
where we filmed some earphones plugged into a laptop computer,
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我們拍攝了一些插在電腦上的耳機。
09:31
and in this case, our goal was to recover the music that was playing on that laptop
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我們的目標是還原出 在手提電腦上所放出的聲音,
09:35
from just silent video
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從這兩個小耳機中的
09:38
of these two little plastic earphones,
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從靜止影片中得到。
09:40
and we were able to do this so well
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並且我們可以做得很好,
09:42
that I could even Shazam our results.
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甚至能夠用聽歌識曲軟體鑑別我們的結果。
09:45
(Laughter)
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(笑聲)
09:49
(Music: "Under Pressure" by Queen)
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(音樂:皇后樂隊 “壓力之下”)
10:01
(Applause)
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(掌聲)
10:06
And we can also push things by changing the hardware that we use.
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我們也可以通過改變硬體來推動事物。
10:11
Because the experiments I've shown you so far
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我給你們看的這些實驗
10:13
were done with a camera, a high-speed camera,
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都使用了攝影機,高速攝影機,
10:15
that can record video about a 100 times faster
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我們可以比大多數手機
10:18
than most cell phones,
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快一百倍地記錄影片。
10:20
but we've also found a way to use this technique
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但是我們也找到了用普通攝影機
10:23
with more regular cameras,
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使用這一項技術的方法。
10:25
and we do that by taking advantage of what's called a rolling shutter.
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我們採用普通照相機 像百葉窗一樣記錄東西優點來記錄。
10:29
You see, most cameras record images one row at a time,
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你們知道,大多數照相機 一段時間記錄一排的圖像,
10:34
and so if an object moves during the recording of a single image,
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所以如果一個物體 只在被記錄的圖像中移動,
10:40
there's a slight time delay between each row,
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在記錄的每一排之間幾乎沒有延遲。
10:43
and this causes slight artifacts
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這樣就可以使物體
10:46
that get coded into each frame of a video.
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被記錄到影片的每一個部分之中。
10:49
And so what we found is that by analyzing these artifacts,
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我們發現透過分析這些東西,
10:53
we can actually recover sound using a modified version of our algorithm.
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實際上只是用了更改過的算法來還原出聲音。
10:58
So here's an experiment we did
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下面就是我們所做的實驗。
11:00
where we filmed a bag of candy
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我們拍攝了一袋糖,
11:01
while a nearby loudspeaker played
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同時邊上有一個擴音器正在播放著
11:03
the same "Mary Had a Little Lamb" music from before,
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與之前相同的“瑪麗有隻小綿羊”。
11:06
but this time, we used just a regular store-bought camera,
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但是這一次我們僅使用從商店買來的攝影機。
11:10
and so in a second, I'll play for you the sound that we recovered,
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馬上我就向你們播放我們還原出的聲音。
11:13
and it's going to sound distorted this time,
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這一次聲音聽起來有一些扭曲,
11:15
but listen and see if you can still recognize the music.
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但是請聽聽看能否分辨出這音樂。
11:19
(Audio: "Mary Had a Little Lamb")
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(聲音:“瑪麗有隻小綿羊”)
11:37
And so, again, that sounds distorted,
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聲音確實被扭曲了,
11:40
but what's really amazing here is that we were able to do this
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但是神奇的是,我們能夠做這個事情,
11:45
with something that you could literally run out
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運用一些用完以後
11:48
and pick up at a Best Buy.
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就可以在 Best Buy 買到的東西。
11:51
So at this point,
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所以在這時
11:52
a lot of people see this work,
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很多人可以看到我們的研究結果,
11:54
and they immediately think about surveillance.
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然後他們立刻會想到監視。
11:57
And to be fair,
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公平的說,
12:00
it's not hard to imagine how you might use this technology to spy on someone.
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不難想到你們可以用這項技術去監視其他人。
12:04
But keep in mind that there's already a lot of very mature technology
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但是要記住早就有許多成熟的技術
12:08
out there for surveillance.
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為監視所準備。
12:09
In fact, people have been using lasers
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事實上,人們數十年來使用雷射
12:12
to eavesdrop on objects from a distance for decades.
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去竊聽別的事物。
12:15
But what's really new here,
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但是,這個技術新穎的地方、
12:18
what's really different,
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完全不同的地方,
12:19
is that now we have a way to picture the vibrations of an object,
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是我們現在有辦法拍攝出物體的振動。
12:23
which gives us a new lens through which to look at the world,
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讓我們獲得了觀察這個世界的新鏡頭,
12:27
and we can use that lens
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並且可以使用這鏡頭,
12:28
to learn not just about forces like sound that cause an object to vibrate,
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不僅僅是為了去瞭解導致物體振動的聲音,
12:33
but also about the object itself.
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還瞭解了物體本身。
12:36
And so I want to take a step back
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所以我想往回退一步
12:38
and think about how that might change the ways that we use video,
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去思考這個技術會如何改變 我們應用影片的方法。
12:42
because we usually use video to look at things,
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因為我們用影片通常來看一些東西,
12:46
and I've just shown you how we can use it
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並且我剛才已經展示如何使用它
12:48
to listen to things.
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去聽一些東西。
12:50
But there's another important way that we learn about the world:
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但是另外有一個我們瞭解世界的重要方法,
12:54
that's by interacting with it.
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那就是和它互動。
12:56
We push and pull and poke and prod things.
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我們推、拉、戳、刺一些事物,
13:00
We shake things and see what happens.
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我們搖動物體來明白發生了什麼事。
13:03
And that's something that video still won't let us do,
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那是影片無法做到的。
13:07
at least not traditionally.
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至少過去不行。
13:09
So I want to show you some new work,
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所以我想向你們展示一些新的成品,
13:11
and this is based on an idea I had just a few months ago,
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這源自我幾個月之前的想法,
13:14
so this is actually the first time I've shown it to a public audience.
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所以這是我第一次公眾展示。
13:17
And the basic idea is that we're going to use the vibrations in a video
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而且基本的想法就是 我們會用影片之中的振動,
13:22
to capture objects in a way that will let us interact with them
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來捕捉物體 在某種程度上這樣可以使我們與物體互動,
13:27
and see how they react to us.
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並且可以知道它們如何對我們進行反應。
13:31
So here's an object,
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這是一個物體。
13:32
and in this case, it's a wire figure in the shape of a human,
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這是一個用線做成的人。
13:36
and we're going to film that object with just a regular camera.
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我們要用普通的相機去拍攝它,
13:39
So there's nothing special about this camera.
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所以這個相機沒有什麼特別之處。
13:41
In fact, I've actually done this with my cell phone before.
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事實上我曾經用我的手機完成過這件事
13:44
But we do want to see the object vibrate,
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但是我們確實希望這個物體振動。
13:47
so to make that happen,
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所以為了做到這點,
13:48
we're just going to bang a little bit on the surface where it's resting
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我們在拍攝的時候
13:51
while we record this video.
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在它放置的地方敲擊。
13:59
So that's it: just five seconds of regular video,
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這就是全部了:一個僅僅五秒鐘的普通影片,
14:03
while we bang on this surface,
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拍攝我們敲擊表面的時候。
14:05
and we're going to use the vibrations in that video
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我們將要用這個影片的震動
14:08
to learn about the structural and material properties of our object,
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去瞭解這個物體的結構和組織組成,
14:13
and we're going to use that information to create something new and interactive.
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然後使用這個訊息 去創造新穎和互動性的東西。
14:24
And so here's what we've created.
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這就是我們所創造的。
14:27
And it looks like a regular image,
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這看起來像一個普通的圖片,
14:29
but this isn't an image, and it's not a video,
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但是這不是圖片也不是影片。
14:32
because now I can take my mouse
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因為我可以用我的游標,
14:35
and I can start interacting with the object.
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也可以和我這個物體互動。
14:44
And so what you see here
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所以你們看到的
14:47
is a simulation of how this object
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是一個我們從來沒看到過的,
14:49
would respond to new forces that we've never seen before,
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關於物體如何對新的力量進行反應。
14:54
and we created it from just five seconds of regular video.
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我們只是使用了五秒鐘的影片。
14:59
(Applause)
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(掌聲)
15:09
And so this is a really powerful way to look at the world,
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所以這是個十分有力的看世界的方法,
15:12
because it lets us predict how objects will respond
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讓我們能推測物體是如何在新環境
15:15
to new situations,
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做出反應的。
15:17
and you could imagine, for instance, looking at an old bridge
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並且可以想像,例如看一個古老的橋樑,
15:20
and wondering what would happen, how would that bridge hold up
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並思考開車經過那座橋時
15:24
if I were to drive my car across it.
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它會如何支撐住。
15:27
And that's a question that you probably want to answer
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那是一個在你開車穿過之前,
15:30
before you start driving across that bridge.
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你會想先知道答案的問題。
15:33
And of course, there are going to be limitations to this technique,
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的確,這項技術還是有侷限性的,
15:37
just like there were with the visual microphone,
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就像視覺麥克風也有缺陷一樣,
15:39
but we found that it works in a lot of situations
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但是我們發現它適用於許多情況,
15:42
that you might not expect,
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你可能沒有想到的,
15:44
especially if you give it longer videos.
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尤其是拍攝更長影片的時候。
15:47
So for example, here's a video that I captured
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例如,這是我拍的一段影片,
15:50
of a bush outside of my apartment,
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是我公寓外的灌木叢。
15:52
and I didn't do anything to this bush,
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我沒有對這灌木叢做什麼事,
15:55
but by capturing a minute-long video,
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但是透過拍攝一段一分鐘的影片,
15:58
a gentle breeze caused enough vibrations
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一陣輕風可以產生足夠的振動,
16:01
that we could learn enough about this bush to create this simulation.
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我們可以足夠地瞭解這個灌木叢 從而創造出這樣的模擬情況。
16:07
(Applause)
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(掌聲)
16:13
And so you could imagine giving this to a film director,
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所以你可以想像將這個技術給一個電影導演,
16:16
and letting him control, say,
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讓他來控制
16:18
the strength and direction of wind in a shot after it's been recorded.
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影片拍攝完後的風力強度和方向。
16:24
Or, in this case, we pointed our camera at a hanging curtain,
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我們也將相機指向了一個掛著的窗簾,
16:29
and you can't even see any motion in this video,
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你幾乎看不到影片中有任何動作,
16:33
but by recording a two-minute-long video,
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但是拍攝兩分鐘的影片後,
16:36
natural air currents in this room
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在這個房間中的天然氣流
16:38
created enough subtle, imperceptible motions and vibrations
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創造了足夠細微、不可被察覺的動作和振動,
16:43
that we could learn enough to create this simulation.
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這樣我們也可以透過振動製造出模擬。
16:48
And ironically,
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可笑的是,
16:50
we're kind of used to having this kind of interactivity
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我們只是在
16:53
when it comes to virtual objects,
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虛擬的物體上,
16:56
when it comes to video games and 3D models,
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電視遊戲和3D模型中使用這種互動。
16:59
but to be able to capture this information from real objects in the real world
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但是僅僅使用簡單普通的影片
17:04
using just simple, regular video,
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去捕捉現實世界中的真實物體,
17:06
is something new that has a lot of potential.
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仍然有很大的潛力。
17:10
So here are the amazing people who worked with me on these projects.
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這裏有許多傑出的人 與我共同研究這些計劃。
17:16
(Applause)
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(掌聲)
17:24
And what I've shown you today is only the beginning.
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我今天展示給你們看的只是個開始。
17:27
We've just started to scratch the surface
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我們僅僅開始挖出表面的一部分,
17:29
of what you can do with this kind of imaging,
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看看這樣的成像技術能做到什麼事。
17:32
because it gives us a new way
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因為它給了我們一個新的方法
17:35
to capture our surroundings with common, accessible technology.
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透過平常可得到的技術去捕捉周圍的東西。
17:40
And so looking to the future,
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所以展望未來,
17:41
it's going to be really exciting to explore
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探索這個技術 可以告訴我們關於這個世界
17:44
what this can tell us about the world.
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會變得格外激動人心。
17:46
Thank you.
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謝謝。
17:47
(Applause)
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(掌聲)
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