Edge detection doesn’t explain line drawing
aaronhertzmann.com
Edge detection doesn’t explain line drawing
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Re: Edge detection doesn’t explain line drawing
#2Re: Edge detection doesn’t explain line drawing
#3The truth is the visual cortex is vast, and not sufficient to explain the human classification and perception of objects visually. Never mind individual neurons or edge perception. Edge detection is an interesting isolated example for study and learning, but you will never come close to explaining human recognition and cognition in such simple terms.
Re: Edge detection doesn’t explain line drawing
#4It's a combination.
Re: Edge detection doesn’t explain line drawing
#5In some cases, simple segmentation fails (like with the shadowed face in the article), and you have to rely on other features.
Re: Edge detection doesn’t explain line drawing
#6The same skepticism could be raised towards letters and words.
If we had invented the photo camera before the paint brush or pen, things might have looked different.
Re: Edge detection doesn’t explain line drawing
#7Re: Edge detection doesn’t explain line drawing
#8As someone (probably like many here) who graduated from a university which taught computer vision and peripheral neuroscience courses, with such titles as "Computational Neuroscience of Vision", I always felt that trying to understand the human brain as a kind of algorithm was a bit of an artefact of computer scientists as they approach biology. The truth is the visual cortex is vast, and not sufficient to explain th…
(incidentally; there’s a fairly deep literature of historians of science that have carefully documented that we describe ourselves as analogous to the most sophisticated technology of the day: see “to lose one’s temper”, “to blow a gasket”, “i got my wires crossed”, “sorry, cache miss”, … as metaphors and idioms of mental state through the centuries that reflect the cool tech of the time in which they were coined )
Re: Edge detection doesn’t explain line drawing
#9At first we assumed that we must have had a bug somewhere because the Fourrier transform told us that our approach was optimal, but after more testing everything matched the expected output. Yet it looked worse.
So we started reverse-engineering the other solutions and, long story short, what they did better is that they added some form of edge-enhancement to the upscaling. Information-theory-wise it actually degraded the image, but subjectively the sharper outlines were just so much nicer to look at and looked correct-er. You felt like you could more easily tell the details even though, again, in a mathematical sense you actually lost information that way.
I don't think it makes a lot of sense to reduce human vision to edge detection (we can still make sense of a blurry image like this one after all: https://static0.makeuseofimages.com/wordpress/wp-content/upl... ) but it's clear to me from empirical evidence that edge-detection is a core aspect of how we parse visual stimuli.
As such I'm a bit confused as to why the author seems to see this as a binary proposition. That being said, I could just be misunderstanding completely the point the author is trying to make.