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

204,073 views ・ 2015-05-05

TED


Please double-click on the English subtitles below to play the video.

Prevodilac: Mile Živković Lektor: Milenka Okuka
00:13
Most of us think of motion as a very visual thing.
0
13373
3349
Većina nas shvata pokret kao nešto izrazito vizuelno.
00:17
If I walk across this stage or gesture with my hands while I speak,
1
17889
5088
Ako hodam po ovoj bini ili mrdam rukama dok govorim,
00:22
that motion is something that you can see.
2
22977
2261
taj pokret je nešto što možete da vidite.
00:26
But there's a world of important motion that's too subtle for the human eye,
3
26255
5482
Ali postoji ceo svet važnih pokreta koji je nevidljiv za ljudsko oko,
00:31
and over the past few years,
4
31737
2041
i proteklih nekoliko godina,
00:33
we've started to find that cameras
5
33778
1997
počeo sam da shvatam da kamere
00:35
can often see this motion even when humans can't.
6
35775
3410
često mogu da vide pokret koji ljudsko oko ne može.
00:40
So let me show you what I mean.
7
40305
1551
Pokazaću vam na šta mislim.
00:42
On the left here, you see video of a person's wrist,
8
42717
3622
Sa leve strane, možete videti snimak nečijeg zgloba,
00:46
and on the right, you see video of a sleeping infant,
9
46339
3147
a sa desne strane, snimak bebe koja spava,
00:49
but if I didn't tell you that these were videos,
10
49486
3146
ali da vam nisam rekao da su ovo video snimci,
00:52
you might assume that you were looking at two regular images,
11
52632
3761
možda biste pomislili da gledate u dve najobičnije slike,
00:56
because in both cases,
12
56393
1672
zato što u oba slučaja,
00:58
these videos appear to be almost completely still.
13
58065
3047
ovi snimci deluju potpuno mirno.
01:02
But there's actually a lot of subtle motion going on here,
14
62175
3885
Zapravo, dosta nevidljivih pokreta imamo ovde,
01:06
and if you were to touch the wrist on the left,
15
66060
2392
i ako biste dotakli zglob na levoj strani,
01:08
you would feel a pulse,
16
68452
1996
osetili biste puls,
01:10
and if you were to hold the infant on the right,
17
70448
2485
a kada biste držali bebu, s desne strane,
01:12
you would feel the rise and fall of her chest
18
72933
2391
ostetili biste podizanje i spuštanje njenih grudi
01:15
as she took each breath.
19
75324
1390
dok udiše i izdiše.
01:17
And these motions carry a lot of significance,
20
77762
3576
Ovi pokreti su od velikog značaja,
01:21
but they're usually too subtle for us to see,
21
81338
3343
ali su obično jako mali da bi ih mi uočili,
01:24
so instead, we have to observe them
22
84681
2276
pa zbog toga, moramo da ih posmatramo
01:26
through direct contact, through touch.
23
86957
2900
kroz direktni kontakt, kroz dodir.
01:30
But a few years ago,
24
90997
1265
Ali pre nekoliko godina,
01:32
my colleagues at MIT developed what they call a motion microscope,
25
92262
4405
moj kolega sa MIT-a je razvio nešto što oni zovu mikroskopom pokreta,
01:36
which is software that finds these subtle motions in video
26
96667
4384
što je zapravo softver koji nalazi ove male pokrete, snima ih
01:41
and amplifies them so that they become large enough for us to see.
27
101051
3562
i uvećava pa time postaju dovoljno veliki da ih mi vidimo.
01:45
And so, if we use their software on the left video,
28
105416
3483
Dakle, ako primenimo softver na levi snimak,
01:48
it lets us see the pulse in this wrist,
29
108899
3250
omogućava nam da vidimo puls na zglobu,
01:52
and if we were to count that pulse,
30
112149
1695
a ako bismo merili puls,
01:53
we could even figure out this person's heart rate.
31
113844
2355
mogli bismo čak i izmeriti otkucaj srca ove osobe.
01:57
And if we used the same software on the right video,
32
117095
3065
A ako primenimo isti softver na snimak desno,
02:00
it lets us see each breath that this infant takes,
33
120160
3227
moći ćemo da vidimo svaki udisaj bebe,
02:03
and we can use this as a contact-free way to monitor her breathing.
34
123387
4137
i možemo ovo da iskoristimo kao nedirektno nadgledanje njenog disanja.
02:08
And so this technology is really powerful because it takes these phenomena
35
128884
5348
Dakle, ova tehnologija je jako moćna, zato što ove pojave
02:14
that we normally have to experience through touch
36
134232
2367
u normalnim uslovima doživljavamo kroz dodir,
02:16
and it lets us capture them visually and non-invasively.
37
136599
2957
i pamtimo ih vizuelno i neinvazivno.
02:21
So a couple years ago, I started working with the folks that created that software,
38
141104
4411
Pre par godina, počeo sam da radim sa ljudima koji su napravili taj softver,
02:25
and we decided to pursue a crazy idea.
39
145515
3367
i odlučili smo da pratimo jednu ludu ideju.
02:28
We thought, it's cool that we can use software
40
148882
2693
Pomislili smo, kul je što možemo da upotrebimo softver
02:31
to visualize tiny motions like this,
41
151575
3135
da predočimo majušne pokrete poput ovog,
02:34
and you can almost think of it as a way to extend our sense of touch.
42
154710
4458
a možemo to shavatiti kao način kojim pojačavamo naš osećaj za dodir.
02:39
But what if we could do the same thing with our ability to hear?
43
159168
4059
Ali šta ako bismo mogli da učinimo isto sa osećajem sluha?
02:44
What if we could use video to capture the vibrations of sound,
44
164508
4665
Šta ako bismo mogli da koristimo video za beleženje zvučnih vibracija,
02:49
which are just another kind of motion,
45
169173
2827
koje su samo druga vrsta pokreta,
02:52
and turn everything that we see into a microphone?
46
172000
3346
i pretvorimo sve što vidimo u mikrofon?
02:56
Now, this is a bit of a strange idea,
47
176236
1971
Sad, ovo je pomalo čudna ideja,
02:58
so let me try to put it in perspective for you.
48
178207
2586
pa me pustite da vam predočim.
03:01
Traditional microphones work by converting the motion
49
181523
3488
Obični mikrofoni funkcionišu tako što pretvaraju vibriranje
03:05
of an internal diaphragm into an electrical signal,
50
185011
3599
unutrašnje dijafragme u elektornski signal,
03:08
and that diaphragm is designed to move readily with sound
51
188610
4318
a ta dijafragma je dizajnirana da se pomera uporedo sa zvukom,
03:12
so that its motion can be recorded and interpreted as audio.
52
192928
4807
pa se njeno vibriranje beleži i interpretira kao audio zapis.
03:17
But sound causes all objects to vibrate.
53
197735
3668
Međutim, zvuk uzrokuje da svi objekti vibriraju.
03:21
Those vibrations are just usually too subtle and too fast for us to see.
54
201403
5480
A te vibracije su obično neprimetne i jako brze za nas da bismo ih uočili.
03:26
So what if we record them with a high-speed camera
55
206883
3738
Dakle, šta ako bi ih beležili kamerom velike brzine,
03:30
and then use software to extract tiny motions
56
210621
3576
a zatim upotrebili softver da pojačamo sićušne vibracije
03:34
from our high-speed video,
57
214197
2090
sa našeg brzog snimka,
03:36
and analyze those motions to figure out what sounds created them?
58
216287
4274
i analiziramo te vibracije da bismo shvatili kakvi ih zvuci stvaraju?
03:41
This would let us turn visible objects into visual microphones from a distance.
59
221859
5449
Ovo bi nam dozvolilo da prebacimo vidljive predmete u vizuelne mikrofone sa distance.
03:49
And so we tried this out,
60
229080
2183
Pa smo ovo i isprobali.
03:51
and here's one of our experiments,
61
231263
1927
Evo jednog od eksperimenata,
gde smo uzeli ovu biljku u saksiji, koju možete da vidite sa desne strane,
03:53
where we took this potted plant that you see on the right
62
233190
2949
03:56
and we filmed it with a high-speed camera
63
236139
2438
i snimili smo kamerom velike brzine,
03:58
while a nearby loudspeaker played this sound.
64
238577
3529
dok je zvučnik u blizini puštao ovaj zvuk.
04:02
(Music: "Mary Had a Little Lamb")
65
242275
8190
(muzika: "Meri je imala malo jagnje")
04:11
And so here's the video that we recorded,
66
251820
2824
A evo snimka koji smo snimili,
04:14
and we recorded it at thousands of frames per second,
67
254644
3924
a snimili smo ga pri 1000 sličica u sekundi,
04:18
but even if you look very closely,
68
258568
2322
ali čak i kada pogledate bliže,
04:20
all you'll see are some leaves
69
260890
1951
sve što vidite su neki listovi
04:22
that are pretty much just sitting there doing nothing,
70
262841
3065
koji jednostavno samo stoje i ne rade bilo šta,
04:25
because our sound only moved those leaves by about a micrometer.
71
265906
4806
zato što je naš zvuk pomerao ove listove samo za mikrometar ili dva.
04:31
That's one ten-thousandth of a centimeter,
72
271103
4276
To je desetohiljaditi deo centimetra,
04:35
which spans somewhere between a hundredth and a thousandth
73
275379
4156
što predstavlja između stotog i hiljaditog dela piksela
04:39
of a pixel in this image.
74
279535
2299
na ovoj slici.
04:41
So you can squint all you want,
75
281881
2887
Dakle, možete škiljiti koliko god želite,
04:44
but motion that small is pretty much perceptually invisible.
76
284768
3335
ali toliko mali pokret je vizuelno prilično nevidljiv.
04:49
But it turns out that something can be perceptually invisible
77
289667
4157
Ali ispostavlja se da nešto što može da bude čulno nevidljivo
04:53
and still be numerically significant,
78
293824
2809
i dalje može biti numerički značajno,
04:56
because with the right algorithms,
79
296633
2002
time što sa adekvatnim algoritmima,
04:58
we can take this silent, seemingly still video
80
298635
3687
možemo uzeti ovaj tih, naizgled miran snimak
05:02
and we can recover this sound.
81
302322
1527
i vratimo ovaj zvuk.
05:04
(Music: "Mary Had a Little Lamb")
82
304690
7384
(muzika: "Meri je imala malo jagnje")
05:12
(Applause)
83
312074
5828
(Aplauz)
05:22
So how is this possible?
84
322058
1939
Kako je ovo moguće?
05:23
How can we get so much information out of so little motion?
85
323997
4344
Kako možemo dobiti toliko informacija iz toliko sitnih pokreta?
05:28
Well, let's say that those leaves move by just a single micrometer,
86
328341
5361
Pa, recimo da se ti listovi pomeraju za jedan mikrometar,
05:33
and let's say that that shifts our image by just a thousandth of a pixel.
87
333702
4308
i recomo da to pomera našu sliku za jedan hiljaditi deo piksela.
05:39
That may not seem like much,
88
339269
2572
To možda ne deluje mnogo,
05:41
but a single frame of video
89
341841
1996
ali jedna sličica snimka
05:43
may have hundreds of thousands of pixels in it,
90
343837
3257
može da sadrži stotine hiljada piksela u sebi,
05:47
and so if we combine all of the tiny motions that we see
91
347094
3454
pa tako ako iskombinujemo sve ove sitne pokrete koje vidimo
05:50
from across that entire image,
92
350548
2298
preko cele slike,
05:52
then suddenly a thousandth of a pixel
93
352846
2623
odjednom hiljaditi deo piksela
05:55
can start to add up to something pretty significant.
94
355469
2775
može doprineti nečemu jako bitnom.
05:58
On a personal note, we were pretty psyched when we figured this out.
95
358870
3635
Lično, bili smo prilično zapanjeni kada smo ovo otkrili.
06:02
(Laughter)
96
362505
2320
(Smeh)
06:04
But even with the right algorithm,
97
364825
3253
Ali i sa pravim algoritmom,
06:08
we were still missing a pretty important piece of the puzzle.
98
368078
3617
i dalje nam je nedostajao jako bitan deo slagalice.
06:11
You see, there are a lot of factors that affect when and how well
99
371695
3604
Vidite, postoji veliki broj faktora koji utiču kada i koliko dobro će
06:15
this technique will work.
100
375299
1997
ova tehika raditi.
06:17
There's the object and how far away it is;
101
377296
3204
U pitanju je objekat i koliko je on daleko;
06:20
there's the camera and the lens that you use;
102
380500
2394
zatim, kamera i sočiva koja koristite;
06:22
how much light is shining on the object and how loud your sound is.
103
382894
4091
koliko je objekat osvetljen i koliko je jak vaš zvuk.
06:27
And even with the right algorithm,
104
387945
3375
I sa odgovarajućim algoritmom,
06:31
we had to be very careful with our early experiments,
105
391320
3390
moramo biti jako pažljivi sa našim prvim eksperimentima,
06:34
because if we got any of these factors wrong,
106
394710
2392
zato što ako bilo koji od ovih faktora bude poremećen,
06:37
there was no way to tell what the problem was.
107
397102
2368
ne postoji način da shvatimo šta je u pitanju.
06:39
We would just get noise back.
108
399470
2647
Zauzvrat bismo dobili samo buku.
06:42
And so a lot of our early experiments looked like this.
109
402117
3320
Pa prema tome, većina naših prvih eksperimenata je ovako izgledala.
06:45
And so here I am,
110
405437
2206
Evo mene,
06:47
and on the bottom left, you can kind of see our high-speed camera,
111
407643
4040
dole levo možete videti kameru velike brzine,
06:51
which is pointed at a bag of chips,
112
411683
2183
koja je usmerena ka kesici čipsa,
06:53
and the whole thing is lit by these bright lamps.
113
413866
2949
a cela stvar je osvetljena ovim jakim lampama.
06:56
And like I said, we had to be very careful in these early experiments,
114
416815
4365
Kao što sam rekao, morali smo da budemo jako pažljivi sa prvim eksperimentima,
07:01
so this is how it went down.
115
421180
2508
i to je ovako izgledalo.
07:03
(Video) Abe Davis: Three, two, one, go.
116
423688
3761
(Snimak) Eb Dejvis: Tri, dva, jedan, kreni.
07:07
Mary had a little lamb! Little lamb! Little lamb!
117
427449
5387
Meri je imala malo jagnje! Malo jagnje! Malo jagnje!
07:12
(Laughter)
118
432836
4500
(Smeh)
07:17
AD: So this experiment looks completely ridiculous.
119
437336
2814
ED: Dakle, ovaj eksperiment je izgledao potpuno smešno.
07:20
(Laughter)
120
440150
1788
(Smeh)
07:21
I mean, I'm screaming at a bag of chips --
121
441938
2345
Mislim, vičem na kesicu čipsa,
07:24
(Laughter) --
122
444283
1551
(Smeh)
07:25
and we're blasting it with so much light,
123
445834
2117
i osvetili smo je toliko jakom svetlošću,
07:27
we literally melted the first bag we tried this on. (Laughter)
124
447951
4479
da smo bukvalno istopili prvu kesicu kada smo probali ovo. (Smeh)
07:32
But ridiculous as this experiment looks,
125
452525
3274
Ali koliko god smešno izgledao ovaj eksperiment,
07:35
it was actually really important,
126
455799
1788
bio je, zapravo, jako bitan,
07:37
because we were able to recover this sound.
127
457587
2926
zato što smo mogli da povratimo zvuk.
07:40
(Audio) Mary had a little lamb! Little lamb! Little lamb!
128
460513
4712
(Audio) Meri je imala malo jagnje! Malo jagnje! Malo jagnje!
07:45
(Applause)
129
465225
4088
(Aplauz)
07:49
AD: And this was really significant,
130
469313
1881
ED: Ovo je bilo značajno,
07:51
because it was the first time we recovered intelligible human speech
131
471194
4119
zato što je to bio prvi put da smo uspeli da povratimo razumljiv ljudski govor
07:55
from silent video of an object.
132
475424
2341
tihog snimka jednog objekta.
07:57
And so it gave us this point of reference,
133
477765
2391
Dakle, ovo nam je dalo ovakve rezultate,
08:00
and gradually we could start to modify the experiment,
134
480156
3871
i vremenom smo mogli da počnemo da modifikujemo eksperiment
08:04
using different objects or moving the object further away,
135
484106
3805
koristeći različite objekte ili pomerajući objekat dalje,
08:07
using less light or quieter sounds.
136
487911
2770
koristeći slabije svetlo ili tiši zvuk.
08:11
And we analyzed all of these experiments
137
491887
2874
Analizirali smo sve ove ekperimente
08:14
until we really understood the limits of our technique,
138
494761
3622
dok nismo zaista shvatili granice naše tehnike,
zato što kada smo jednom shvatili granice,
08:18
because once we understood those limits,
139
498383
1950
08:20
we could figure out how to push them.
140
500333
2346
smislili bismo kako da ih gurnemo dalje.
08:22
And that led to experiments like this one,
141
502679
3181
A to nas je dovelo do eksperimenta poput ovog,
08:25
where again, I'm going to speak to a bag of chips,
142
505860
2739
gde ja, ponovo, govorim kesi čipsa,
08:28
but this time we've moved our camera about 15 feet away,
143
508599
4830
ali ovog puta smo pomerili kameru oko 4,5 m dalje,
08:33
outside, behind a soundproof window,
144
513429
2833
van, iza zvučno izolovanog prozora,
08:36
and the whole thing is lit by only natural sunlight.
145
516262
2803
i cela ova stvar je osvetljena samo prirodnom svetlošću.
08:40
And so here's the video that we captured.
146
520529
2155
I evo snimka koji smo snimili.
08:44
And this is what things sounded like from inside, next to the bag of chips.
147
524450
4559
A ovako se stvari čuju iznutra, pored kese čipsa.
08:49
(Audio) Mary had a little lamb whose fleece was white as snow,
148
529009
5038
(Audio) Meri je imala malo jagnje, čije je runo bilo belo kao sneg
08:54
and everywhere that Mary went, that lamb was sure to go.
149
534047
5619
i kuda god je Meri išla, jagnje je išlo s njom.
08:59
AD: And here's what we were able to recover from our silent video
150
539666
4017
ED: A ovo smo uspeli da povratimo sa našeg tihog snimka
09:03
captured outside behind that window.
151
543683
2345
snimljenog van, iza tog prozora.
09:06
(Audio) Mary had a little lamb whose fleece was white as snow,
152
546028
4435
(Audio) Meri je imala malo jagnje čije je runo bilo belo kao sneg,
09:10
and everywhere that Mary went, that lamb was sure to go.
153
550463
5457
i kuda god je Meri išla, jagnje je išlo s njom.
09:15
(Applause)
154
555920
6501
(Aplauz)
09:22
AD: And there are other ways that we can push these limits as well.
155
562421
3542
ED: A postoje, takođe, i drugi načini kako da pomerimo granice.
09:25
So here's a quieter experiment
156
565963
1798
Time, ovde imamo tiši eksperiment,
09:27
where we filmed some earphones plugged into a laptop computer,
157
567761
4110
gde smo snimili jedne slušalice priključene na laptop,
09:31
and in this case, our goal was to recover the music that was playing on that laptop
158
571871
4110
gde je naš cilj bio da muziku koja je puštena na laptopu
09:35
from just silent video
159
575981
2299
povratimo sa tihog snimka
09:38
of these two little plastic earphones,
160
578280
2507
sa ove dve male plastične bubice,
09:40
and we were able to do this so well
161
580787
2183
i uspeli smo da uradimo to tako dobro
09:42
that I could even Shazam our results.
162
582970
2461
da smo mogli naše rezultate koristiti čak i na Šazemu.
09:45
(Laughter)
163
585431
2411
(Smeh)
09:49
(Music: "Under Pressure" by Queen)
164
589191
10034
(Muzika: "Pod pritiskom", grupa Kvin)
10:01
(Applause)
165
601615
4969
(Aplauz)
10:06
And we can also push things by changing the hardware that we use.
166
606584
4551
A možemo i poboljšati stvari menjajući hardver koji koristimo.
10:11
Because the experiments I've shown you so far
167
611135
2461
Jer su eksperimenti koje sam vam pokazao do sada
10:13
were done with a camera, a high-speed camera,
168
613596
2322
napravljeni kamerom, kamerom velike brzine,
10:15
that can record video about a 100 times faster
169
615918
2879
koja može da napravi snimak oko 100 puta brže
10:18
than most cell phones,
170
618797
1927
u odnosu na većinu mobilnih telefona,
10:20
but we've also found a way to use this technique
171
620724
2809
ali takođe smo našli način da upotrebimo ovu tehniku
10:23
with more regular cameras,
172
623533
2230
sa mnogo običnijim kamerama,
10:25
and we do that by taking advantage of what's called a rolling shutter.
173
625763
4069
i uradili smo to tako što smo iskoristili nešto što se zove pokretni okidač.
10:29
You see, most cameras record images one row at a time,
174
629832
4798
Vidite, većina fotoaparata snima slike jedan po jedan red,
10:34
and so if an object moves during the recording of a single image,
175
634630
5702
tako da ako se predmet pomeri tokom snimanja jedne slike,
10:40
there's a slight time delay between each row,
176
640344
2717
postoji kratko kašnjenje između svakog reda
10:43
and this causes slight artifacts
177
643061
3157
i zbog ovoga ostaju blagi tragovi
10:46
that get coded into each frame of a video.
178
646218
3483
koji se kodiraju u svaki frejm snimka.
10:49
And so what we found is that by analyzing these artifacts,
179
649701
3806
Otkrili smo da analizom ovih tragova
10:53
we can actually recover sound using a modified version of our algorithm.
180
653507
4615
zapravo možemo povratiti zvuk koristeći izmenjenu verziju našeg algoritma.
10:58
So here's an experiment we did
181
658122
1912
Evo eksperimenta koji smo uradili,
11:00
where we filmed a bag of candy
182
660034
1695
gde smo snimili kesicu bombona
11:01
while a nearby loudspeaker played
183
661729
1741
dok se iz zvučnika u blizini čulo
11:03
the same "Mary Had a Little Lamb" music from before,
184
663470
2972
ista muzika od pre: "Meri je imala malo jagnje",
11:06
but this time, we used just a regular store-bought camera,
185
666442
4203
ali ovog puta smo koristili običan fotoaparat iz prodavnice
11:10
and so in a second, I'll play for you the sound that we recovered,
186
670645
3174
i sada ću vam pustiti zvuk koji smo povratili,
11:13
and it's going to sound distorted this time,
187
673819
2050
i ovog puta će zvučati izmenjeno,
11:15
but listen and see if you can still recognize the music.
188
675869
2836
ali slušajte i vidite da li još uvek možete da prepoznate muziku.
11:19
(Audio: "Mary Had a Little Lamb")
189
679723
6223
(Audio: "Meri je imala malo jagnje")
11:37
And so, again, that sounds distorted,
190
697527
3465
Opet, to zvuči izmenjeno,
11:40
but what's really amazing here is that we were able to do this
191
700992
4386
ali ovde je zaista neverovatno to što smo ovo mogli da uradimo
11:45
with something that you could literally run out
192
705378
2626
sa nečim što bukvalno možete otići
11:48
and pick up at a Best Buy.
193
708004
1444
i kupiti u lokalnoj prodavnici bele tehnike.
11:51
So at this point,
194
711122
1363
U ovom trenutku,
11:52
a lot of people see this work,
195
712485
1974
mnogi ljudi vide kako ovo radi
11:54
and they immediately think about surveillance.
196
714459
3413
i odmah pomisle na nadgledanje.
11:57
And to be fair,
197
717872
2415
Da budem iskren, nije teško zamisliti
12:00
it's not hard to imagine how you might use this technology to spy on someone.
198
720287
4133
kako biste mogli koristiti ovu tehnologiju da špijunirate nekoga.
12:04
But keep in mind that there's already a lot of very mature technology
199
724420
3947
Ali imajte na umu da trenutno već postoji dosta veoma razvijene tehnologije
12:08
out there for surveillance.
200
728367
1579
za nadgledanje.
12:09
In fact, people have been using lasers
201
729946
2090
Zapravo, ljudi su decenijama koristili lasere
12:12
to eavesdrop on objects from a distance for decades.
202
732036
2799
kako bi prisluškivali sa udaljenosti.
12:15
But what's really new here,
203
735978
2025
Ali ono što je ovde zaista novo,
12:18
what's really different,
204
738003
1440
zaista drugačije,
12:19
is that now we have a way to picture the vibrations of an object,
205
739443
4295
je da sada imamo način da prikažemo vibracije na predmetu,
12:23
which gives us a new lens through which to look at the world,
206
743738
3413
što nam daje novi objektiv kroz koji možemo gledati svet
12:27
and we can use that lens
207
747151
1510
i taj objektiv možemo koristiti
12:28
to learn not just about forces like sound that cause an object to vibrate,
208
748661
4899
da saznamo, ne samo o silama poput zvuka od kojih predmet vibrira,
12:33
but also about the object itself.
209
753560
2288
nego i o samom predmetu.
12:36
And so I want to take a step back
210
756975
1693
Želim da se udaljim
12:38
and think about how that might change the ways that we use video,
211
758668
4249
i razmislim o tome kako to može da promeni način na koji koristimo video,
12:42
because we usually use video to look at things,
212
762917
3553
jer video obično koristimo da posmatramo stvari
12:46
and I've just shown you how we can use it
213
766470
2322
i pokazao sam vam upravo kako ga možemo koristiti
12:48
to listen to things.
214
768792
1857
da slušamo stvari.
12:50
But there's another important way that we learn about the world:
215
770649
3971
Ali tu je važan način na koji saznajemo stvari o svetu -
12:54
that's by interacting with it.
216
774620
2275
kroz interakciju.
12:56
We push and pull and poke and prod things.
217
776895
3111
Guramo i vučemo i pritiskamo i čačkamo stvari.
13:00
We shake things and see what happens.
218
780006
3181
Tresemo ih da vidimo šta će se desiti.
13:03
And that's something that video still won't let us do,
219
783187
4273
A video nam još uvek ne dozvoljava to,
13:07
at least not traditionally.
220
787460
2136
makar ne u tradicionalnom smislu.
13:09
So I want to show you some new work,
221
789596
1950
Želim da vam pokažem neke nove radove,
13:11
and this is based on an idea I had just a few months ago,
222
791546
2667
a ovo je zasnovano na zamisli koju sam imao pre nekoliko meseci,
13:14
so this is actually the first time I've shown it to a public audience.
223
794213
3301
ovo je zapravo prvi put da to pokazujem pred publikom.
13:17
And the basic idea is that we're going to use the vibrations in a video
224
797514
5363
Osnovna ideja je da ćemo koristiti vibracije u video snimku
13:22
to capture objects in a way that will let us interact with them
225
802877
4481
da snimimo predmete na način koji će nam dozvoliti interkaciju sa njima
13:27
and see how they react to us.
226
807358
1974
i da vidimo kako reaguju na nas.
13:31
So here's an object,
227
811120
1764
Evo predmeta,
13:32
and in this case, it's a wire figure in the shape of a human,
228
812884
3832
i u ovom slučaju to je žičana figura u obliku čoveka,
13:36
and we're going to film that object with just a regular camera.
229
816716
3088
i taj predmet ćemo snimiti običnim fotoaparatom.
13:39
So there's nothing special about this camera.
230
819804
2124
Dakle, nema ničeg posebnog u vezi sa ovim fotoaparatom.
13:41
In fact, I've actually done this with my cell phone before.
231
821928
2961
Zapravo, ovo sam pre radio sa svojim telefonom.
13:44
But we do want to see the object vibrate,
232
824889
2252
Ali želimo da vidimo da predmet vibrira,
13:47
so to make that happen,
233
827141
1133
i kako bi se to desilo,
13:48
we're just going to bang a little bit on the surface where it's resting
234
828274
3346
samo malo ćemo udariti površinu gde predmet stoji
13:51
while we record this video.
235
831620
2138
dok snimamo ovaj video.
13:59
So that's it: just five seconds of regular video,
236
839398
3671
To je to: samo pet sekundi običnog video snimka,
14:03
while we bang on this surface,
237
843069
2136
dok lupamo po površini
14:05
and we're going to use the vibrations in that video
238
845205
3513
i iskoristićemo vibracije iz tog videa,
14:08
to learn about the structural and material properties of our object,
239
848718
4544
kako bismo saznali strukturna i materijalna svojstva našeg predmeta
14:13
and we're going to use that information to create something new and interactive.
240
853262
4834
i iskoristićemo te informacije da stvorimo nešto novo i interaktivno.
14:24
And so here's what we've created.
241
864866
2653
Evo šta smo stvorili.
14:27
And it looks like a regular image,
242
867519
2229
Izgleda kao obična slika,
14:29
but this isn't an image, and it's not a video,
243
869748
3111
ali ovo nije slika i nije video,
14:32
because now I can take my mouse
244
872859
2368
jer sada mogu da uzmem miš
14:35
and I can start interacting with the object.
245
875227
2859
i da budem u interakciji sa ovim predmetom.
14:44
And so what you see here
246
884936
2357
Ovde možete videti
14:47
is a simulation of how this object
247
887389
2226
simulaciju toga kako bi ovaj predmet
14:49
would respond to new forces that we've never seen before,
248
889615
4458
odgovorio na nove sile koje do sada nismo videli,
14:54
and we created it from just five seconds of regular video.
249
894073
3633
i to smo stvorili iz samo pet sekundi običnog video snimka.
14:59
(Applause)
250
899249
4715
(Aplauz)
15:09
And so this is a really powerful way to look at the world,
251
909421
3227
Ovo je zaista moćan način da se posmatra svet
15:12
because it lets us predict how objects will respond
252
912648
2972
jer nam dozvoljava da predvidimo kako će predmeti odgovoriti
15:15
to new situations,
253
915620
1823
na nove situacije
15:17
and you could imagine, for instance, looking at an old bridge
254
917443
3473
i možete da zamislite, na primer, kako gledate stari most
15:20
and wondering what would happen, how would that bridge hold up
255
920916
3527
i pitate se šta bi se desilo, kako bi se ponašao taj most
15:24
if I were to drive my car across it.
256
924443
2833
kada bih prešao preko njega svojim automobilom.
15:27
And that's a question that you probably want to answer
257
927276
2774
A to je pitanje na koje verovatno želite da odgovorite
15:30
before you start driving across that bridge.
258
930050
2560
pre nego što počnete da vozite preko tog mosta.
15:33
And of course, there are going to be limitations to this technique,
259
933988
3272
Naravno, biće nekoliko ograničenja za ovu tehniku,
15:37
just like there were with the visual microphone,
260
937260
2462
kao što ih je bilo i sa vizuelnim mikrofonom,
15:39
but we found that it works in a lot of situations
261
939722
3181
ali otkrili smo da funkcioniše u mnogim situacijama
15:42
that you might not expect,
262
942903
1875
gde to ne biste očekivali,
15:44
especially if you give it longer videos.
263
944778
2768
naročito ako radite sa dužim snimcima,
15:47
So for example, here's a video that I captured
264
947546
2508
Na primer, evo video zapisa koji sam napravio
15:50
of a bush outside of my apartment,
265
950054
2299
gde je žbun ispred mog stana,
15:52
and I didn't do anything to this bush,
266
952353
3088
a njemu nisam radio ništa
15:55
but by capturing a minute-long video,
267
955441
2705
osim što sam ga snimao jedan minut,
15:58
a gentle breeze caused enough vibrations
268
958146
3378
lagan povetarac izazvao je dovoljno vibracija
16:01
that we could learn enough about this bush to create this simulation.
269
961524
3587
da smo mogli da saznamo dovoljno o ovom žbunu da napravimo simulaciju.
16:07
(Applause)
270
967270
6142
(Aplauz)
16:13
And so you could imagine giving this to a film director,
271
973412
2972
Možete da zamislite da ovo date filmskom režiseru
16:16
and letting him control, say,
272
976384
1719
i date mu da kontroliše, na primer,
16:18
the strength and direction of wind in a shot after it's been recorded.
273
978103
4922
jačinu i pravac vetra u snimku nakon što je on nastao.
16:24
Or, in this case, we pointed our camera at a hanging curtain,
274
984810
4535
Ili, u ovom slučaju, uperili smo fotoaparat u zavesu koja visi
16:29
and you can't even see any motion in this video,
275
989345
4129
i u ovom snimku čak ni ne možete da vidite bilo kakvo kretanje,
16:33
but by recording a two-minute-long video,
276
993474
2925
ali snimanjem videa dugog dva minuta,
16:36
natural air currents in this room
277
996399
2438
prirodne vazdušne struje u prostoriji
16:38
created enough subtle, imperceptible motions and vibrations
278
998837
4412
stvorile su dovoljno suptilnog, neprimetnog kretanja i vibracija
16:43
that we could learn enough to create this simulation.
279
1003249
2565
da možemo da saznamo dovoljno da stvorimo ovu simulaciju.
16:48
And ironically,
280
1008243
2366
Ironično je to
16:50
we're kind of used to having this kind of interactivity
281
1010609
3088
kako smo nekako priviknuti da imamo ovakvu vrstu interaktivnosti
16:53
when it comes to virtual objects,
282
1013697
2647
kod virtuelnih predmeta,
16:56
when it comes to video games and 3D models,
283
1016344
3297
što se tiče video igara i 3D modela,
16:59
but to be able to capture this information from real objects in the real world
284
1019641
4404
ali kako bismo dobili ove informacije iz pravih predmeta iz stvarnosti,
17:04
using just simple, regular video,
285
1024045
2817
koristeći proste, obične video snimke,
17:06
is something new that has a lot of potential.
286
1026862
2183
to je nešto novo što ima dosta potencijala.
17:10
So here are the amazing people who worked with me on these projects.
287
1030410
4904
Evo neverovatnih ljudi koji su sa mnom radili na ovom projektu.
17:16
(Applause)
288
1036057
5596
(Aplauz)
17:24
And what I've shown you today is only the beginning.
289
1044819
3057
Ono što sam vam pokazao danas je samo početak.
17:27
We've just started to scratch the surface
290
1047876
2113
Samo smo zagrebali površinu toga
17:29
of what you can do with this kind of imaging,
291
1049989
2972
što možete da uradite sa ovim načinom prikazivanja slika,
17:32
because it gives us a new way
292
1052961
2286
jer nam to daje novi metod
17:35
to capture our surroundings with common, accessible technology.
293
1055342
4724
da snimimo svoju okolinu, prostom, dostupnom tehnologijom.
17:40
And so looking to the future,
294
1060066
1929
Gledajući u budućnost,
17:41
it's going to be really exciting to explore
295
1061995
2037
biće zaista zanimljiva za istraživanje toga
17:44
what this can tell us about the world.
296
1064032
1856
šta nam ovo može reći o svetu.
17:46
Thank you.
297
1066381
1204
Hvala vam.
17:47
(Applause)
298
1067610
6107
(Aplauz)
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7