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Ancient secrets of computer vision

pjreddie.com

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Re: Ancient secrets of computer vision

#13
While the content is definitely great, its outer looks are not so much. I am afraid I value whatever scraps of non-computer, human vision I still have left with me a tad more than learning those cool eldritch secrets... although the reader mode definitely helps.

Re: Ancient secrets of computer vision

#14

While the content is definitely great, its outer looks are not so much. I am afraid I value whatever scraps of non-computer, human vision I still have left with me a tad more than learning those cool eldritch secrets... although the reader mode definitely helps.

[deleted]

Re: Ancient secrets of computer vision

#15
It's nice, but missing the most valuable (and simplest) take from computer vision: the Hough transforms.

Let's take the circle Hough transform as it's one of the most enlightening ones!

Say you are looking for a circle of a given diameter. After a binarization to make the edge stand out, make all the potential points "vote" for a circle center.

The method is simple: using a matrix, you +1 all the points that are as far from this point as the radius of the circle will allow.

Do this for every point, and take the max: https://en.wikipedia.org/wiki/Circle_Hough_Transform

Simple, and works in guaranteed time.

Extension 1: if you don't know the radius, apply iteratively for a range of values, then again, take the max: if you imagine how it works (or code it as an example then animate the result), it's like doing a "mathematical" focus.

Extension 2: if it's too costly to do a dense exploration of the space of values for the radius, while you know there's only one circle, do a gradient descent on the increase.

Extension 3: If there are more that one circle, other techniques exist - the easiest to picture are based on the maximization of variance of the distribution of values in the matrix resulting from the binarization, but you can also use 2d lattices and other fun tricks.

Re: Ancient secrets of computer vision

#16
post #15

It's nice, but missing the most valuable (and simplest) take from computer vision: the Hough transforms. Let's take the circle Hough transform as it's one of the most enlightening ones! Say you are looking for a circle of a given diameter. After a binarization to make the edge stand out, make all the potential points "vote" for a circle center. The method is simple: using a matrix, you +1 all the points that are as f…

Hough transform is awesome and it was patented in 1962!

Re: Ancient secrets of computer vision

#17
post #5
post #2

Content is solid. I'm afraid I can't ignore the author's resume link... https://pjreddie.com/static/Redmon%20Resume.pdf

Hm. Do you think this is deliberate to filter out people with certain prejudices? Or do they genuinely think it’s a good design?

YOLO was such a shake up of the computer vision space that he could probably get hired just about anywhere with a resume crudely written in crayon.

Re: Ancient secrets of computer vision

#18
post #15

It's nice, but missing the most valuable (and simplest) take from computer vision: the Hough transforms. Let's take the circle Hough transform as it's one of the most enlightening ones! Say you are looking for a circle of a given diameter. After a binarization to make the edge stand out, make all the potential points "vote" for a circle center. The method is simple: using a matrix, you +1 all the points that are as f…

The Hough is a good one! Also Invariant Moments: https://en.m.wikipedia.org/wiki/Image_moment

Re: Ancient secrets of computer vision

#19

While the content is definitely great, its outer looks are not so much. I am afraid I value whatever scraps of non-computer, human vision I still have left with me a tad more than learning those cool eldritch secrets... although the reader mode definitely helps.

Then you should definitely not go to YouTube and search for "vaporwave". Definitely definitely definitely.
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