6 ms·

Akiyoshi's Illusion Pages

292 points by mabynogy 10y ago

pcurve 10y ago
Something so refreshing about this unapologetically 1996 styled web site and vast amount of incredible content. This is a great find.
- LeoPanthera 10y ago
  "Web 1.0" sites also tend to work surprisingly well on mobile.
  - apricot 10y ago
    It's almost as if they were using a semantic markup language rather than a visual description language...
    - siddboots 10y ago
      I think you've wearing some serious rose-tinted glasses if you think that web 1.0's html was more semantic focused than today's. Even this example is full of <FONT> tags and align="center" attributes.
- deleted 10y ago
  [deleted]
- mwfj 10y ago
  I miss the 1996-1997 type web sites. Ads and money has changed the web so much. I recently had the idea to start a like 1994-style Yahoo-style web site that only links to sites which fulfill these conditions: a) they have a lot of quality content b) they only have minimal or no ads (absolutely no signups, freemium sites, 14-day trials etc). c) no obnoxious self-advertising of a company's own brand (e.g. "Will It Blend? | Presented by Blendtec"). d) (this one is hard to quantify, but it's a kind of "I know it when I see it" thing) they were made with love and a desire to spread thoughts and creations.. rather than a desire for making money. Obviously this directory site would not be a vehicle for making money. I also don't want this to be a hipster coolness thing. It's not the retro-ugly layouts I'm after, it's the content. Stupid? Does it already exist? The site that I came across that triggered this thought was http://www.americanradiohistory.com/ http://www.americanradiohistory.com/ .
  - sosuke 10y ago
    What you're talking about making is how Yahoo! started out. As a directory of the web. Curated by humans. If you start one please share a link.
tobr 10y ago
Many of these are fantastic, I could swear some of them used actual animation. For example http://www.psy.ritsumei.ac.jp/~akitaoka/kagero3e.html http://www.psy.ritsumei.ac.jp/~akitaoka/kagero3e.html What causes the appearance of movement?
- peteretep 10y ago
  I suspect it's your brain trying to reconcile misleading shadow/highlight information.
  - kpil 10y ago
    I thought it was misrepresentating the shadows and highlights as the "negative" afterglow you get after something has moved on the retina.
cwilkes 10y ago
I can't get the rotating rays one to work. Just stays stationary. All others are fine.
- cyberferret 10y ago
  Similar here. Got it to work somewhat by staring at a fixed point on the image and using my mouse to scroll the page up and down slightly.
pwinnski 10y ago
Having seen the rotating snakes illusion before, I decided to stare at it, playing with the focus of my eyes until the illusion of motion stopped. Once it did, I found that many of the other illusions also didn't work. Also, I have a headache, and everything not on my screen seems slightly unfocused. Clearly I tried a bit too hard!
- natoliniak 10y ago
  On one hand I also felt challenged to find a way to make it stop, but on the other hand, i also had a feeling that if i win i would end up with a migraine. thanks for reaffirming that it is possible and sparing me a headache.
  - moron4hire 10y ago
    It's just an eye strain headache. It goes away with rest. Migraines are a different thing.
    - kaybe 10y ago
      If anyone wants eyestrain, try this: http://www.lutanho.net/play/magiceyetetris.html http://www.lutanho.net/play/magiceyetetris.html
- interfixus 10y ago
  I found that I could actually stop the snakes moving by staring intently at them. However, they easily started rotating again if I let my focus drift a bit. Yes, could probably induce a migraine if I kept at it for while.
  - moron4hire 10y ago
    Most of the images are different exploitations of the "peripheral illusory movement" effect. Alternating bands of contrasting color--high, medium high, low, medium low--gives the impression of movement, bit only in periphery vision.
- 10y ago
coldcode 10y ago
After looking this page everything seems to be moving.
mrpopo 10y ago
For context, he got a little boost recently from his "strawberry cake" illusion tweet : https://twitter.com/AkiyoshiKitaoka/status/836743598469070849 https://twitter.com/AkiyoshiKitaoka/status/83674359846907084...
wmboy 10y ago
Aghh, this is what it feels like to have a migraine with aura, except that with a migraine your vision looks like this no matter what you're looking at.
codezero 10y ago
This is a little off topic but seems as good a place as any to ask: Is anyone working on computer vision that is "tricked" by illusions? I'm curious because it seems like a good way to test how accurately computer vision maps to human vision (then again, I'm not even sure that's a goal!)
- Baeocystin 10y ago
  Sort of. Computer vision is susceptible to illusions, although as you can see in the link, not the same type that we are. https://www.extremetech.com/extreme/195789-bad-news-future-computers-are-easily-tricked-by-optical-illusions-too https://www.extremetech.com/extreme/195789-bad-news-future-c...
- tim_hutton 10y ago
  In computer vision there is a well-known problem of estimating the color of the lighting. I worked on detecting the player's skin color for a recent computer game. We decided not to use an RGB camera for pretty much the same reason as seen in the strawberry illusion - the computer would see those strawberries as gray. An image with unknown lighting might look fine to a human but it's hard for a computer to estimate the actual color of objects without also seeing objects of known color, such as a color card.
- soravux 10y ago
  Human vision works well because our brain has an incredible quantity of priors to guide it, that is similar past experiences that explain most of what we are seeing. When your eyes see something, only a small amount of information is passed to your brain (like motion, for example). Your brain "fills up" the missing pieces with what he's used to. That's why we don't see the blind spot created by our optical nerve entrance in the eye and often miss things that are hiding in plain sight without motion. Illusions are due to the deception of our vision priors. Our brain expects something, makes you see something this way, but it's not what is happening in reality (maybe because it was engineered to deceive those expectations, as the images in this thread link). This is because the mental model we have of a standard "sight" doesn't model well those examples, our brain was not trained to work this out, I guess because it has no advantages in doing so (in terms of evolution or learning as a kid). Our brain is only trained to extract information efficiently on "plausible images" (lit by sun-like light, taken on the earth, etc.), you can't feed it random noise or it will try to explain it with things it knows (which is called Pareidolia). In machine learning vision, we re-learn, usually from scratch (or fine-tune), at each experiment. This generates (or modify) the priors learned. Think of the priors as the "default(s)" image (in terms of complex internal representation, not in terms of pixels) that helps you think about the problem at hand. If you have a motion detection/tracking problem, this optimal default information representation will be different from the default information most useful for classifying or segmenting. What I want to say with those examples is that machine learning computer vision is prone to illusions, that is images that defeat (are too far away, or not well explained by) its internal representation space and/or default representation. Also, each algorithm (let it be neural networks, SVM, or anything, really) has a different internal representation, so different images will be illusions for them. An illusion for one model won't necessarily be an illusion for another one. The thing is, we are far from mastering advanced machine learning, in the sense that we don't have optimality proofs for capacity, architecture and filters on deep neural networks for a given task, for example. There's a lot of recent research on those illusions--for example, adversarial examples or networks. It seems to indicate that those illusions are far from human vision illusions and seems to be due to the mathematical nature of machine learning, for example adding small noise (sometimes with a lower magnitude than the smallest representable value by standard images formats!) to a correctly classified image can result in a wrong and very certain prediction. The most proeminent viral example of this on the internet was the school bus becoming with high certainty an ostrich after some small noise was added to the image. Other examples can be found in the introduction of [1]. [1] https://openai.com/blog/adversarial-example-research/ https://openai.com/blog/adversarial-example-research/
jpfed 10y ago
Am I the only person who is made nauseous by the rotating snakes illusion? I had to hit the back button before the page was done loading.
- rangibaby 10y ago
  > Should you feel dizzy, you had better leave this page immediately
martyvis 10y ago
"A bulge" is brilliant! Pinch-zooming on a phone and lining up the square lines against the screen edge is mind blowing.
speps 10y ago
Nice paper from 2008 here exploring how to make specific patterns : http://graphics.csie.ncku.edu.tw/SAI/ http://graphics.csie.ncku.edu.tw/SAI/
moron4hire 10y ago
My senior undergraduate research thesis was based on the illusions Dr. Kitaoka had constructed. I tested people's ability to perform tasks that required them to understand heightmap data given one of three randomly selected renderers: a top-down, completely flat map with no height rendering as a control; a similar rendering but with Akiyoshi's "A Bulge" illusion generated on the fly for each "hill"; and an isometric rendering where the hills were rendered in 2.5D. I was able to show that the illusion method was about 95% as effective at conveying heightmap data as the isometric map, while being no more computationally complex than the flat map. At the time (2005), it was one of the first direct uses of optical illusion in computer graphics. It was also one of the first papers to discuss the importance of changing graphics techniques to extend battery life on mobile devices. EDIT: forgot I had put up all my stuff into a Github repo a few years ago: https://github.com/capnmidnight/optical-illusions-in-cg/blob/master/final_draft.pdf https://github.com/capnmidnight/optical-illusions-in-cg/blob...
glandium 10y ago
Some of them don't move at all for me... except while scrolling the page.

292 points by mabynogy 10y ago

Something so refreshing about this unapologetically 1996 styled web site and vast amount of incredible content. This is a great find.

LeoPanthera 10y ago
"Web 1.0" sites also tend to work surprisingly well on mobile.
- apricot 10y ago
  It's almost as if they were using a semantic markup language rather than a visual description language...
  - siddboots 10y ago
    I think you've wearing some serious rose-tinted glasses if you think that web 1.0's html was more semantic focused than today's. Even this example is full of <FONT> tags and align="center" attributes.
deleted 10y ago
[deleted]
mwfj 10y ago
I miss the 1996-1997 type web sites. Ads and money has changed the web so much. I recently had the idea to start a like 1994-style Yahoo-style web site that only links to sites which fulfill these conditions: a) they have a lot of quality content b) they only have minimal or no ads (absolutely no signups, freemium sites, 14-day trials etc). c) no obnoxious self-advertising of a company's own brand (e.g. "Will It Blend? | Presented by Blendtec"). d) (this one is hard to quantify, but it's a kind of "I know it when I see it" thing) they were made with love and a desire to spread thoughts and creations.. rather than a desire for making money. Obviously this directory site would not be a vehicle for making money. I also don't want this to be a hipster coolness thing. It's not the retro-ugly layouts I'm after, it's the content. Stupid? Does it already exist? The site that I came across that triggered this thought was http://www.americanradiohistory.com/ http://www.americanradiohistory.com/ .
- sosuke 10y ago
  What you're talking about making is how Yahoo! started out. As a directory of the web. Curated by humans. If you start one please share a link.

tobr 10y ago

Many of these are fantastic, I could swear some of them used actual animation. For example http://www.psy.ritsumei.ac.jp/~akitaoka/kagero3e.html http://www.psy.ritsumei.ac.jp/~akitaoka/kagero3e.html What causes the appearance of movement?

peteretep 10y ago
I suspect it's your brain trying to reconcile misleading shadow/highlight information.
- kpil 10y ago
  I thought it was misrepresentating the shadows and highlights as the "negative" afterglow you get after something has moved on the retina.

cwilkes 10y ago

I can't get the rotating rays one to work. Just stays stationary. All others are fine.

cyberferret 10y ago
Similar here. Got it to work somewhat by staring at a fixed point on the image and using my mouse to scroll the page up and down slightly.

pwinnski 10y ago

Having seen the rotating snakes illusion before, I decided to stare at it, playing with the focus of my eyes until the illusion of motion stopped. Once it did, I found that many of the other illusions also didn't work. Also, I have a headache, and everything not on my screen seems slightly unfocused. Clearly I tried a bit too hard!

natoliniak 10y ago
On one hand I also felt challenged to find a way to make it stop, but on the other hand, i also had a feeling that if i win i would end up with a migraine. thanks for reaffirming that it is possible and sparing me a headache.
- moron4hire 10y ago
  It's just an eye strain headache. It goes away with rest. Migraines are a different thing.
  - kaybe 10y ago
    If anyone wants eyestrain, try this: http://www.lutanho.net/play/magiceyetetris.html http://www.lutanho.net/play/magiceyetetris.html
interfixus 10y ago
I found that I could actually stop the snakes moving by staring intently at them. However, they easily started rotating again if I let my focus drift a bit. Yes, could probably induce a migraine if I kept at it for while.
- moron4hire 10y ago
  Most of the images are different exploitations of the "peripheral illusory movement" effect. Alternating bands of contrasting color--high, medium high, low, medium low--gives the impression of movement, bit only in periphery vision.
10y ago

coldcode 10y ago

After looking this page everything seems to be moving.

mrpopo 10y ago

For context, he got a little boost recently from his "strawberry cake" illusion tweet : https://twitter.com/AkiyoshiKitaoka/status/836743598469070849 https://twitter.com/AkiyoshiKitaoka/status/83674359846907084...

wmboy 10y ago

Aghh, this is what it feels like to have a migraine with aura, except that with a migraine your vision looks like this no matter what you're looking at.

codezero 10y ago

This is a little off topic but seems as good a place as any to ask: Is anyone working on computer vision that is "tricked" by illusions? I'm curious because it seems like a good way to test how accurately computer vision maps to human vision (then again, I'm not even sure that's a goal!)

Baeocystin 10y ago
Sort of. Computer vision is susceptible to illusions, although as you can see in the link, not the same type that we are. https://www.extremetech.com/extreme/195789-bad-news-future-computers-are-easily-tricked-by-optical-illusions-too https://www.extremetech.com/extreme/195789-bad-news-future-c...
tim_hutton 10y ago
In computer vision there is a well-known problem of estimating the color of the lighting. I worked on detecting the player's skin color for a recent computer game. We decided not to use an RGB camera for pretty much the same reason as seen in the strawberry illusion - the computer would see those strawberries as gray. An image with unknown lighting might look fine to a human but it's hard for a computer to estimate the actual color of objects without also seeing objects of known color, such as a color card.
soravux 10y ago
Human vision works well because our brain has an incredible quantity of priors to guide it, that is similar past experiences that explain most of what we are seeing. When your eyes see something, only a small amount of information is passed to your brain (like motion, for example). Your brain "fills up" the missing pieces with what he's used to. That's why we don't see the blind spot created by our optical nerve entrance in the eye and often miss things that are hiding in plain sight without motion. Illusions are due to the deception of our vision priors. Our brain expects something, makes you see something this way, but it's not what is happening in reality (maybe because it was engineered to deceive those expectations, as the images in this thread link). This is because the mental model we have of a standard "sight" doesn't model well those examples, our brain was not trained to work this out, I guess because it has no advantages in doing so (in terms of evolution or learning as a kid). Our brain is only trained to extract information efficiently on "plausible images" (lit by sun-like light, taken on the earth, etc.), you can't feed it random noise or it will try to explain it with things it knows (which is called Pareidolia). In machine learning vision, we re-learn, usually from scratch (or fine-tune), at each experiment. This generates (or modify) the priors learned. Think of the priors as the "default(s)" image (in terms of complex internal representation, not in terms of pixels) that helps you think about the problem at hand. If you have a motion detection/tracking problem, this optimal default information representation will be different from the default information most useful for classifying or segmenting. What I want to say with those examples is that machine learning computer vision is prone to illusions, that is images that defeat (are too far away, or not well explained by) its internal representation space and/or default representation. Also, each algorithm (let it be neural networks, SVM, or anything, really) has a different internal representation, so different images will be illusions for them. An illusion for one model won't necessarily be an illusion for another one. The thing is, we are far from mastering advanced machine learning, in the sense that we don't have optimality proofs for capacity, architecture and filters on deep neural networks for a given task, for example. There's a lot of recent research on those illusions--for example, adversarial examples or networks. It seems to indicate that those illusions are far from human vision illusions and seems to be due to the mathematical nature of machine learning, for example adding small noise (sometimes with a lower magnitude than the smallest representable value by standard images formats!) to a correctly classified image can result in a wrong and very certain prediction. The most proeminent viral example of this on the internet was the school bus becoming with high certainty an ostrich after some small noise was added to the image. Other examples can be found in the introduction of [1]. [1] https://openai.com/blog/adversarial-example-research/ https://openai.com/blog/adversarial-example-research/

jpfed 10y ago

Am I the only person who is made nauseous by the rotating snakes illusion? I had to hit the back button before the page was done loading.

rangibaby 10y ago
> Should you feel dizzy, you had better leave this page immediately

martyvis 10y ago

"A bulge" is brilliant! Pinch-zooming on a phone and lining up the square lines against the screen edge is mind blowing.

speps 10y ago

Nice paper from 2008 here exploring how to make specific patterns : http://graphics.csie.ncku.edu.tw/SAI/ http://graphics.csie.ncku.edu.tw/SAI/

moron4hire 10y ago

My senior undergraduate research thesis was based on the illusions Dr. Kitaoka had constructed. I tested people's ability to perform tasks that required them to understand heightmap data given one of three randomly selected renderers: a top-down, completely flat map with no height rendering as a control; a similar rendering but with Akiyoshi's "A Bulge" illusion generated on the fly for each "hill"; and an isometric rendering where the hills were rendered in 2.5D. I was able to show that the illusion method was about 95% as effective at conveying heightmap data as the isometric map, while being no more computationally complex than the flat map. At the time (2005), it was one of the first direct uses of optical illusion in computer graphics. It was also one of the first papers to discuss the importance of changing graphics techniques to extend battery life on mobile devices. EDIT: forgot I had put up all my stuff into a Github repo a few years ago: https://github.com/capnmidnight/optical-illusions-in-cg/blob/master/final_draft.pdf https://github.com/capnmidnight/optical-illusions-in-cg/blob...

glandium 10y ago

Some of them don't move at all for me... except while scrolling the page.