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What's the best CV course nowadays that comes with videos, assignments, hws, etc.? It used to be the one taught by Justin Johnson at UMich [0]. But the publicly available videos have been last updated in 2019. [0]: https://web.eecs.umich.edu/~justincj/teaching/eecs498/FA2020...
[0] https://uni-tuebingen.de/fakultaeten/mathematisch-naturwisse...
Content is solid. I'm afraid I can't ignore the author's resume link... https://pjreddie.com/static/Redmon%20Resume.pdf
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…
It comes with a wonderful demonstration tool that allows you to apply the various included algorithms to images and tweak the parameters in real-time – including the Hough transform. A great tool for helping to understand how these kinds of algorithms work!
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.
Content is solid. I'm afraid I can't ignore the author's resume link... https://pjreddie.com/static/Redmon%20Resume.pdf
Earlier quoted context omitted.
Hm. Do you think this is deliberate to filter out people with certain prejudices? Or do they genuinely think it’s a good design?
Countersignalling. By deviating from the “professional” look so ostentatiously, they signal that they are so good that they don’t need to use the usual look.
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…
A "faint" circle will often score worse than 2 high-contrast parallel lines that happen to be the right distance apart, since the lines manage to trigger pixels along 20% of a circle's arc and their contrast massively inflates their score compared to the faint circle (higher edge pixel density).
It seems like there should be a simple way to weight the results by how dispersed within the circle's arc the pixels are, but I've never dug any further, after hitting this problem I had to move on.
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…
1. The most valuable take from computer vision
2. The simplest take from computer vision
Not to mention this is rarely useful unless you're in a specific context where you're looking for circles in an image.
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…
I agree it's very cool, but I have found it to be surprisingly poor in certain scenarios. A "faint" circle will often score worse than 2 high-contrast parallel lines that happen to be the right distance apart, since the lines manage to trigger pixels along 20% of a circle's arc and their contrast massively inflates their score compared to the faint circle (higher edge pixel density). It seems like there should be a s…