TEDGlobal 2012
Ramesh Raskar: Imaging at a trillion frames per second
Ramesh Raskar: Et kamera der tager en billion billeder per sekund
Filmed:
Readability: 4
5,395,201 views
Ramesh Raskar præsenterer femtofotografering, en ny type billedbehandling så hurtig at det viser verden en billion billeder per sekund, så detajleret at det viser selve lyset i bevægelse. Denne teknologi kan en dag blive brugt til at bygge kameraer der kan kigge "rundt" om hjørner eller se ind i kroppen uden røntgen.
Ramesh Raskar - Femto-photographer
Photography is about creating images by recording light. At the MIT media lab, professor Ramesh Raskar and his team members have invented a camera that can photograph light itself as it moves at, well, the speed of light. Full bio
Photography is about creating images by recording light. At the MIT media lab, professor Ramesh Raskar and his team members have invented a camera that can photograph light itself as it moves at, well, the speed of light. Full bio
Double-click the English transcript below to play the video.
00:16
Doc Edgerton inspired us with awe and curiosity
0
902
5978
Doc Edgarton inspirerede os med ærefrygt og nysgerrighed
00:22
with this photo of a bullet piercing through an apple,
1
6880
5262
med dette foto af en kugle der gennemborer et æble,
00:28
and exposure just a millionth of a second.
2
12142
4878
og eksponeringen er kun en milliontedel af et sekund.
00:32
But now, 50 years later, we can go a million times faster
3
17020
7307
Men nu, 50 år senere, kan vi være en million gange hurtigere
00:40
and see the world not at a million,
4
24327
3596
og se verden, ikke ved en milliontedel,
00:43
or a billion,
5
27923
1810
eller en milliardtedel,
00:45
but one trillion frames per second.
6
29733
3435
men en billion billeder per sekund.
00:49
I present you a new type of photography,
7
33168
4385
Jeg fremlægger en ny type af fotografering,
00:53
femto-photography,
8
37553
2059
femto-fotografering,
00:55
a new imaging technique so fast
9
39612
4600
en ny billeddannelses teknik der er så hurtig
01:00
that it can create slow motion videos of light in motion.
10
44212
5201
at det kan skabe slow motion videoer af bevægende lys.
01:05
And with that, we can create cameras
11
49413
2738
Og med det, kan vi skabe kameraer
01:08
that can look around corners,
12
52151
2145
der kan se rundt om hjørner,
01:10
beyond line of sight
13
54296
1997
hinsides horisonten
01:12
or see inside our body without an X-ray,
14
56293
4393
eller se ind i vores kroppe uden røntgenstråler,
01:16
and really challenge what we mean by a camera.
15
60686
5401
og virkelig udfordre hvad vi mener med et kamera.
01:21
Now if I take a laser pointer and turn it on and off
16
66087
3511
Hvis vi nu tager en laser pegepind og tænder og slukker den
01:25
in one trillionth of a second --
17
69598
2827
i en billiontedel af et sekund --
01:28
which is several femtoseconds --
18
72425
2812
hvilket er adskillige femtosekunder --
01:31
I'll create a packet of photons
19
75237
2280
skaber jeg en pakke af fotoner
01:33
barely a millimeter wide,
20
77517
2350
knap nok en millimeter brede,
01:35
and that packet of photons, that bullet,
21
79867
2926
og den pakke af fotoner, den kugle,
01:38
will travel at the speed of light,
22
82793
1950
rejser med lysets hastighed,
01:40
and, again, a million times faster than an ordinary bullet.
23
84743
4508
og, igen, en million gange hurtigere end en almindelig kugle.
01:45
Now, if you take that bullet and take this packet of photons
24
89251
4906
Hvis man tager den kugle og kigger på denne pakke fotoner
01:50
and fire into this bottle,
25
94157
3173
og skyder ind i denne flaske,
01:53
how will those photons shatter into this bottle?
26
97330
4534
hvordan vil de fotoner smadre ind i denne flaske?
01:57
How does light look in slow motion?
27
101864
4224
Hvordan ser lys ud i slow motion?
02:21
Now, the whole event -- (Applause)
28
126041
3658
Men, hele hændelsen -- (Bifald)
02:25
(Applause)
29
129699
4219
(Bifald)
02:29
Now, remember, the whole event
30
133918
2603
Husk nu, at hele hændelsen
02:32
is effectively taking place in less than a nanosecond
31
136521
3383
faktisk folder sig ud i løbet af mindre en et nanosekund
02:35
— that's how much time it takes for light to travel —
32
139904
2336
-- så lang tid tager det for lys at rejse --
02:38
but I'm slowing down in this video by a factor of 10 billion
33
142240
4500
men jeg sætter hastigheden ned i denne video med en faktor på 10 milliarder
02:42
so you can see the light in motion.
34
146740
3673
så man kan se lyset i bevægelse.
02:46
But, Coca-Cola did not sponsor this research. (Laughter)
35
150413
4621
Men, Coca-Cola sponsorerede ikke denne forskning. (Latter)
02:50
Now, there's a lot going on in this movie,
36
155034
2047
Nu sker der meget i denne film,
02:52
so let me break this down and show you what's going on.
37
157081
2362
så lad mig lige udspecificere det og vise jer hvad der sker.
02:55
So, the pulse enters the bottle, our bullet,
38
159443
3240
Så, impulsen kommer ind i flasken, vores kugle,
02:58
with a packet of photons that start traveling through
39
162683
2562
med en pakke fotoner der begyndte at rejse gennem
03:01
and that start scattering inside.
40
165245
1837
og begynder at sprede sig derinde.
03:02
Some of the light leaks, goes on the table,
41
167082
2231
Noget af lyset lækker, kommer på bordet,
03:05
and you start seeing these ripples of waves.
42
169313
2787
og man begynder at se disse krusning af bølger.
03:08
Many of the photons eventually reach the cap
43
172100
2881
Mange af fotonerne når til sidst kapslen
03:10
and then they explode in various directions.
44
174981
2914
og så eksploderer de i forskellige retninger.
03:13
As you can see, there's a bubble of air,
45
177895
1912
Og som I kan se, er der en luftboble,
03:15
and it's bouncing around inside.
46
179807
1666
og den bumper rundt derinde.
03:17
Meanwhile, the ripples are traveling on the table,
47
181473
2474
I mellemtiden, rejser krusningerne på bordet,
03:19
and because of the reflections at the top,
48
183947
1869
og på grund af refleksionerne på toppen,
03:21
you see at the back of the bottle, after several frames,
49
185816
3634
kan man se på bagsiden af flasken, efter adskillige billeder,
03:25
the reflections are focused.
50
189450
2902
bliver refleksionerne fokuserede.
03:28
Now, if you take an ordinary bullet
51
192352
5894
Hvis man nu tager en almindelig kugle
03:34
and let it go the same distance and slow down the video
52
198246
3401
og lader den tilbagelægge den samme afstand og forsinker hastigheden på videoen
03:37
again by a factor of 10 billion, do you know
53
201647
2549
igen med en faktor af 10 milliarder, ved I
03:40
how long you'll have to sit here to watch that movie?
54
204196
5725
hvor lang tid I skal sidde der for at se filmen?
03:45
A day, a week? Actually, a whole year.
55
209921
4388
En dag, en uge? Faktisk, et helt år.
03:50
It'll be a very boring movie — (Laughter) —
56
214309
3914
Det vil være en utrolig kedelig film -- (Latter) --
03:54
of a slow, ordinary bullet in motion.
57
218223
4052
af en langsom, almindelig kugle i bevægelse.
03:58
And what about some still-life photography?
58
222275
4603
Og hvad med noget stille dyrelivs fotografering?
04:08
You can watch the ripples again washing over the table,
59
232770
5352
Man kan se krusningerne der igen skyller hen over bordet,
04:14
the tomato and the wall in the back.
60
238122
2913
tomaten og væggen i baggrunden.
04:16
It's like throwing a stone in a pond of water.
61
241035
4224
Det er ligesom at kaste en sten i en dam.
04:23
I thought, this is how nature paints a photo,
62
247197
3890
Jeg tænkte, det er sådan naturen maler et billede,
04:26
one femto frame at a time,
63
251087
2587
et femto billede af gangen,
04:29
but of course our eye sees an integral composite.
64
253674
5392
men selvfølgelig ser vores øje en sammensat integral.
04:34
But if you look at this tomato one more time,
65
259066
3126
Men hvis man ser på denne tomat endnu en gang,
04:38
you will notice, as the light washes over the tomato,
66
262192
2516
vil man lægge mærke til, at mens lyset skyller hen over tomaten,
04:40
it continues to glow. It doesn't become dark.
67
264708
2891
bliver den ved med at gløde. Den bliver ikke mørk.
04:43
Why is that? Because the tomato is actually ripe,
68
267599
3548
Hvorfor det? Fordi tomaten faktisk er moden,
04:47
and the light is bouncing around inside the tomato,
69
271147
2101
og lyset kastes rundt inden i tomaten,
04:49
and it comes out after several trillionths of a second.
70
273248
4466
og den kommer ud efter adskillige billiontedele sekunder.
04:53
So, in the future, when this femto-camera
71
277714
2633
Så, i fremtiden, når dette femtokamera
04:56
is in your camera phone,
72
280347
2092
er i ens kameratelefon,
04:58
you might be able to go to a supermarket
73
282439
1710
er man måske i stand til at gå i supermarkedet
05:00
and check if the fruit is ripe without actually touching it.
74
284149
4040
og se om frugten er moden uden egentlig at røre den.
05:04
So how did my team at MIT create this camera?
75
288189
5330
Så hvordan skabte mit team på MIT dette kamera?
05:09
Now, as photographers, you know,
76
293519
1967
Jamen, som fotografer, ved I,
05:11
if you take a short exposure photo, you get very little light,
77
295486
4061
at hvis man tager et billede med kort eksponering, får man meget lidt lys,
05:15
but we're going to go a billion times faster
78
299547
2206
men vi er en trillion gange hurtigere
05:17
than your shortest exposure,
79
301753
1856
end jeres korteste eksponering,
05:19
so you're going to get hardly any light.
80
303609
1800
så man får nærmest ingen lys.
05:21
So, what we do is we send that bullet,
81
305409
1843
Så, det vi gør er at vi sender den kugle,
05:23
those packet of photons, millions of times,
82
307252
2549
den pakke af fotoner, millioner af gange,
05:25
and record again and again with very clever synchronization,
83
309801
3107
og optager igen og igen med meget dygtig synkronisering,
05:28
and from the gigabytes of data,
84
312908
2091
og fra de gigabyte af data,
05:30
we computationally weave together
85
314999
2116
væver vi dem beregningsteknisk sammen
05:33
to create those femto-videos I showed you.
86
317115
3465
for at skabe disse femto videoer jeg viste jer.
05:36
And we can take all that raw data
87
320580
2540
Og vi kan tage al den rå data
05:39
and treat it in very interesting ways.
88
323120
2895
og behandle det på en meget interessant måde.
05:41
So, Superman can fly.
89
326015
1841
Så, Superman kan flyve.
05:43
Some other heroes can become invisible,
90
327856
2462
Nogen andre helte kan blive usynlige,
05:46
but what about a new power for a future superhero:
91
330318
5098
men hvad med en ny kraft til en fremtidig superhelt:
05:51
to see around corners?
92
335416
2498
til at se om hjørner?
05:53
The idea is that we could shine some light on the door.
93
337914
4673
Ideen er at vi kunne skinne noget lys på døren.
05:58
It's going to bounce, go inside the room,
94
342587
2675
Det vil springe tilbage, gå tilbage ind i lokalet,
06:01
some of that is going to reflect back on the door,
95
345262
2430
noget af det vil reflektere tilbage på døren,
06:03
and then back to the camera,
96
347692
1507
og så tilbage til kameraet,
06:05
and we could exploit these multiple bounces of light.
97
349199
3488
og vi kunne udnytte disse mange forskellige lys tilbagekast.
06:08
And it's not science fiction. We have actually built it.
98
352687
2397
Og det er ikke science fiction. Vi har faktisk bygget den.
06:10
On the left, you see our femto-camera.
99
355084
2384
Til venstre kan I se vores femtokamera.
06:13
There's a mannequin hidden behind a wall,
100
357468
2379
Der er en simpel mannequin bag en væg,
06:15
and we're going to bounce light off the door.
101
359847
2982
og vi vil kaste noget lys tilbage fra døren.
06:18
So after our paper was published
102
362829
1948
Så efter vores artikel blev offentliggjort
06:20
in Nature Communications,
103
364777
1934
i Nature Communications,
06:22
it was highlighted by Nature.com,
104
366711
1915
blev den fremhævet af Nature.com,
06:24
and they created this animation.
105
368626
2563
og de lavede denne animation.
06:27
(Music)
106
371189
6402
(Musik)
06:33
We're going to fire those bullets of light,
107
377591
3461
Vi vil skyde disse lyskugler,
06:36
and they're going to hit this wall,
108
381052
3263
og de vil ramme denne væg,
06:40
and because the packet of the photons,
109
384315
2655
og på grund af pakken med fotoner,
06:42
they will scatter in all the directions,
110
386970
2297
vil de sprede sig i alle retninger,
06:45
and some of them will reach our hidden mannequin,
111
389267
2248
og nogle af dem vil nå vores mannequin,
06:47
which in turn will again scatter that light,
112
391515
2879
der til gengæld igen vil sprede det lys,
06:50
and again in turn the door will reflect
113
394394
3686
og til gengæld vil døren reflektere
06:53
some of that scattered light,
114
398080
2072
noget af det spredte lys,
06:56
and a tiny fraction of the photons will actually
115
400152
2744
og en lille brøkdel af fotonerne vil faktisk
06:58
come back to the camera, but most interestingly,
116
402896
2284
komme tilbage til kameraet, men mest interessant,
07:01
they will all arrive at a slightly different time slot.
117
405180
3746
vil de ankomme på et lidt andet tidspunkt.
07:04
(Music)
118
408926
4577
(Musik)
07:09
And because we have a camera that can run so fast,
119
413503
2817
Og fordi vi har et kamera der er så hurtigt,
07:12
our femto-camera, it has some unique abilities.
120
416320
3106
vores femtokamera, har det nogle unikke egenskaber.
07:15
It has very good time resolution,
121
419426
2906
Det har en rigtig god tid opløsning
07:18
and it can look at the world at the speed of light.
122
422332
3518
og det kan se på verden med lysets hastighed.
07:21
And this way, we know the distances, of course to the door,
123
425850
3545
Og på denne måde, kender vi afstanden, selvfølgelig til døren,
07:25
but also to the hidden objects,
124
429395
1894
men også til de skjulte genstande,
07:27
but we don't know which point corresponds
125
431289
1595
men vi ved ikke hvilket punkt der svarer til
07:28
to which distance.
126
432884
2322
hvilken afstand.
07:31
(Music)
127
435206
3240
(Musik)
07:34
By shining one laser, we can record one raw photo, which,
128
438446
3944
Ved at lyse en laser, kan vi optage en råt billede, som,
07:38
you look on the screen, doesn't really make any sense,
129
442390
2450
i kigger på skærmen, ikke rigtigt giver nogen mening,
07:40
but then we will take a lot of such pictures,
130
444840
1880
men så vil vi tage en masse af den slags billeder,
07:42
dozens of such pictures, put them together,
131
446720
2419
dusinvis af den slags billeder, sætte dem sammen,
07:45
and try to analyze the multiple bounces of light,
132
449139
2678
og prøve at analysere de adskillige tilbagespring af lys,
07:47
and from that, can we see the hidden object?
133
451817
3416
og af det, kan vi se et skjult objekt?
07:51
Can we see it in full 3D?
134
455233
2919
Kan vi se det i fuld 3D?
07:54
So this is our reconstruction. (Music)
135
458152
2636
Så dette er vores rekonstruktion. (Musik)
07:56
(Music)
136
460788
3458
(Musik)
08:00
(Music) (Applause)
137
464246
8308
(Musik) (Bifald)
08:08
Now we have some ways to go before we take this
138
472554
2611
Nu har er der stadig et stykke vej før vi tager dette
08:11
outside the lab on the road, but in the future,
139
475165
3197
med ud af laboratoriet og med på vejen, men i fremtiden,
08:14
we could create cars that avoid collisions
140
478362
2834
kunne vi skabe biler der forhindrer ulykker
08:17
with what's around the bend,
141
481196
2216
med det der er om hjørnet,
08:19
or we can look for survivors in hazardous conditions
142
483412
3914
eller vi kan se efter overlevende i farlige miljøer,
08:23
by looking at light reflected through open windows,
143
487326
4278
ved at kigge på lyset der reflekteres ud af åbne vinduer,
08:27
or we can build endoscopes that can see
144
491604
2625
eller vi kan bygge endoskoper der kan se
08:30
deep inside the body around occluders,
145
494229
3270
dybt ind i kroppen rundt om indelukker,
08:33
and also for cardioscopes.
146
497499
1876
og også for kardioskoper.
08:35
But of course, because of tissue and blood,
147
499375
2501
Men selvfølgelig, på grund af væv og blod,
08:37
this is quite challenging, so this is really a call
148
501876
2187
er det temmelig udfordrende, så dette er egentlig et kald
08:39
for scientists to start thinking about femto-photography
149
504063
2853
til alle videnskabsfolk for at begynde at tænke på femto fotografering
08:42
as really a new imaging modality to solve
150
506916
2589
som en virkelig ny billeddannelses behandlingsmetode at behandle
08:45
the next generation of health imaging problems.
151
509505
3577
den næste generation af helbreds billeddannelses problemer med.
08:48
Now, like Doc Edgerton, a scientist himself,
152
513082
3881
Men, ligesom Doc Edgerton, der selv var videnskabsmand,
08:52
science became art, an art of ultra-fast photography,
153
516963
5176
blev videnskab en kunstart, en kunstart af ultra hurtig fotografering,
08:58
and I realized that all the gigabytes of data
154
522139
3464
og jeg opdagede at alle de gigabyte af data
09:01
that we're collecting every time
155
525603
2004
som vi indsamler hver gang
09:03
is not just for scientific imaging, but we can also do
156
527607
3443
ikke kun er til videnskabelig , men vi kan også lave
09:06
a new form of computational photography
157
531050
3780
en ny slags beregningsteknisk fotografering
09:10
with time-lapse and color-coding,
158
534830
4139
med tids-overlap og farve kodning,
09:14
and we look at those ripples. Remember,
159
538969
2770
og vi kigger på de krusninger. Husk nu,
09:17
the time between each of those ripples is only
160
541739
2675
at tiden mellem hver er de krusninger kun er
09:20
a few trillionths of a second.
161
544414
4343
et par billiontedele af et sekund.
09:24
But there's also something funny going on here.
162
548757
1956
Men der sker også noget sjovt her.
09:26
When you look at the ripples under the cap,
163
550713
2354
Når man kigger på krusningerne under kapslen,
09:28
the ripples are moving away from us.
164
553067
3620
flytter krusningerne sig væk fra os.
09:32
The ripples should be moving towards us.
165
556687
2149
Krusningerne burde komme i vores retning.
09:34
What's going on here?
166
558836
1767
Hvad sker der her?
09:36
It turns out, because we're recording
167
560603
1958
Det viser sig, fordi vi optager
09:38
nearly at the speed of light,
168
562561
4547
næsten med lysets hastighed,
09:43
we have strange effects,
169
567108
2070
har vi mærkelige effekter,
09:45
and Einstein would have loved to see this picture.
170
569178
4031
og Einstein ville have elsket at se dette billede.
09:49
The order at which events take place in the world
171
573209
3269
Rækkefølgen som disse hændelser sker i, i verden
09:52
appear in the camera with sometimes reversed order,
172
576478
4568
viser sig nogen gange i omvendt rækkefølge i kameraet,
09:56
so by applying the corresponding space and time warp,
173
581046
3359
så ved at tilføje den korresponderende plads og tid forvrængning,
10:00
we can correct for this distortion.
174
584405
4045
kan vi rette op på denne forvrængning.
10:04
So whether it's for photography around corners,
175
588450
4241
Så om det er til at fotografere om hjørner med,
10:08
or creating the next generation of health imaging,
176
592691
4308
eller at skabe den næste generation af medicinsk billedanalyse,
10:12
or creating new visualizations,
177
596999
2680
eller skabe ny visualiseringer,
10:15
since our invention, we have open-sourced
178
599679
3559
siden vores opdagelse, har vi open-sourced
10:19
all the data and details on our website, and our hope
179
603238
3699
alle dataene og detaljerne på vores webside, og vores håb er
10:22
is that the DIY, the creative and the research community
180
606937
6636
at gør-det-selv folket, det kreative og det videnskabelige samfund
10:29
will show us that we should stop obsessing about
181
613573
3803
vil vise os, at vi skal holde op med at være besat af
10:33
the megapixels in cameras — (Laughter) —
182
617376
3240
megapixlerne i kameraerne -- (Latter) --
10:36
and start focusing on the next dimension in imaging.
183
620616
5030
og begynde at fokusere på den næste dimension billedbehandling.
10:41
It's about time. Thank you. (Applause)
184
625646
4534
Det handler om tid. Tak. (Bifald)
10:46
(Applause)
185
630180
10205
(Bifald)
ABOUT THE SPEAKER
Ramesh Raskar - Femto-photographerPhotography is about creating images by recording light. At the MIT media lab, professor Ramesh Raskar and his team members have invented a camera that can photograph light itself as it moves at, well, the speed of light.
Why you should listen
In 1964 MIT professor Harold Edgerton, pioneer of stop-action photography, famously took a photo of a bullet piercing an apple using exposures as short as a few nanoseconds. Inspired by his work, Ramesh Raskar and his team set out to create a camera that could capture not just a bullet (traveling at 850 meters per second) but light itself (nearly 300 million meters per second).
Stop a moment to take that in: photographing light as it moves. For that, they built a camera and software that can visualize pictures as if they are recorded at 1 trillion frames per second. The same photon-imaging technology can also be used to create a camera that can peer "around" corners , by exploiting specific properties of the photons when they bounce off surfaces and objects.
Among the other projects that Raskar is leading, with the MIT Media Lab's Camera Culture research group, are low-cost eye care devices, a next generation CAT-Scan machine and human-computer interaction systems.
Papers:
Andreas Velten, Thomas Willwacher, Otkrist Gupta, Ashok Veeraraghavan, Moungi G. Bawendi and Ramesh Raskar, “Recovering ThreeDimensional Shape around a Corner using Ultra-Fast Time-of-Flight Imaging.” Nature Communications, March 2012
Andreas Velten, Adrian Jarabo, Belen Masia, Di Wu, Christopher Barsi, Everett Lawson, Chinmaya Joshi, Diego Gutierrez, Moungi G. Bawendi and Ramesh Raskar, "Ultra-fast Imaging for Light in Motion" (in progress). http://femtocamera.info
Ramesh Raskar | Speaker | TED.com