7 ms·
Ancient secrets of computer vision
- redeyed 5y agoWatched this lectures 2 years ago and It's pretty solid!
- syntaxing 5y agoWhoa sounds interesting! I always wondered what happened to him after giving up on YOLO because he felt it was against his morals. I honestly give him props because he probably could of capitalized on his work if he wanted to and play his cards right.
- yboris 5y agoSorry, grammar pet peeve of mine: "could have" not "could of" :) cheers!
- cyber_kinetist 5y agoFrom the lab homepage it seems that he eventually graduated with a PhD (https://raivn.cs.washington.edu/people.html https://raivn.cs.washington.edu/people.html). A few years ago he said he’d thought about quitting research and opening a vegan cafe or something. Not sure what he’s planning to do now though.
- bloqs 5y agoContent is solid. I'm afraid I can't ignore the author's resume link... https://pjreddie.com/static/Redmon%20Resume.pdf https://pjreddie.com/static/Redmon%20Resume.pdf
- version_five 5y agoSolid - certainly memorable. I like it a lot better than those ones with meters that show your levels of various skills
- jstx1 5y agoHm. Do you think this is deliberate to filter out people with certain prejudices? Or do they genuinely think it’s a good design?
- bozzy 5y agoI'd say it is a good example of how not to take yourself too seriously. The contrast is cool too! He's achieved quite a bit and expressed it in such a cool and playful way.
- dekhn 5y agoit helped him get an internship at Google where he worked on computer vision. the person who hired him said it was a great resume and he was the smarted guy he ever worked with.
- canjobear 5y agoCountersignalling. 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.
- randomluck040 5y agoIt’s PJ Reddie after all, the YOLO guy.
- monocasa 5y agoFor those who need a bit more context, YOLO the object recognition ML model. He can work anywhere he wants.
- timy2shoes 5y agoIf he wanted to work on computer vision instead of a vegan restaurant (or something similar, I forget exactly).
- jointpdf 5y ago
- named-user 5y agoFor the jobs he's going to be successful at, he doesn't need a CV.
- mdp2021 5y agoWell, it is almost unforgettable, is not it? "Outstanding".
- orangepurple 5y agoExtremely knowledgeable and talented people can still harbor mental illnesses.
- bozzy 5y agoI can attest to this and I have been making reference back to this course a lot and I have recommended it to a few people starting this CV journey. Joseph is also the creator of Yolo, so go figure!
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- Joker_vD 5y agoWhile 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 5y ago[deleted]
- jerf 5y agoThen you should definitely not go to YouTube and search for "vaporwave". Definitely definitely definitely.
- lolsal 5y agoAlternative opinion: The design of the site is a welcome breath of fresh air. Not every site needs gobs of whitespace, neutral colors and advertisements.
- csdvrx 5y agoIt'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 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.
- sasaf5 5y agoThe Hough is a good one! Also Invariant Moments: https://en.m.wikipedia.org/wiki/Image_moment https://en.m.wikipedia.org/wiki/Image_moment
- zwieback 5y agoHough transform is awesome and it was patented in 1962!
- amelius 5y ago> After a binarization to make the edge stand out, make all the potential points "vote" for a circle center. It's even simpler to make artificial neurons vote for a circle center. You don't need the binarization step, and you can apply the method to other shapes as well.
- edge17 5y agoThe hough transform generalizes to other shapes as well
- batguano 5y agoThat logo is exceptionally hideous.
- fortyseven 5y agoIn the best way, for me. Gives it personality.
- rg111 5y agoWhat'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/ https://web.eecs.umich.edu/~justincj/teaching/eecs498/FA2020...
- ibrarmalik 5y agoI like Andreas Geiger’s lectures on U. Tübingen [0]. Quite recent, and I think the topics they cover are good. [0] https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/computer-vision/ https://uni-tuebingen.de/fakultaeten/mathematisch-naturwisse...
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- Edmond 5y agoHausdorff distance is also a simple probabilistic technique that works quite well: https://ecommons.cornell.edu/bitstream/handle/1813/6165/92-1321.pdf https://ecommons.cornell.edu/bitstream/handle/1813/6165/92-1... In a different life I toyed with it a bit: http://pugoob.blogspot.com/2008/01/pugoob-image-search-tool.html http://pugoob.blogspot.com/2008/01/pugoob-image-search-tool....
- monocasa 5y agoA really ancient secret, one of the grey beards I learned a lot from early in my career told me about how he got CV running on an Apple II way back in the day on the cheap. He decapped a DRAM, and carefully stuck a lens on it. They're not just susceptible to cosmic rays; without the package regular old visible light rays can cause bit flips too. If you look at CMOS sensors these days they actually have quite a bit in common with DRAM.
- dapids 5y agoI think I'm missing the point. What does any of this have to do with computer vision?
- LukeShu 5y agoHe was able to turn a RAM chip into a camera, allowing the computer to process a video "feed" simply by polling the right bits in RAM. On a device that would normally be considered much too primitive to do any image processing.
- dougabug 5y agoThere was a Byte Magazine article by Steve Ciarcia, in Sept 1983, entitled “A 64K-bit dynamic RAM chip is the visual sensor in this digital image camera,” describing how to do exactly this hack. https://archive.org/details/byte-magazine-1983-09/mode/2up https://archive.org/details/byte-magazine-1983-09/mode/2up
- 5y ago
- ffhhj 5y agoBack in the day, before Vuforia implemented volumetric tracking, I developed my own Pepsi can detector for an augmented reality app, just processing filters.
- MauranKilom 5y agoIn terms of practical application (e.g. in industry), the biggest bang for your buck is "get the illumination right". Surprised this never appears in the course (at least from glancing over the syllabus and some slides). Most CV tasks are borderline impossible if your input is acquired under uncontrollable lighting. Whereas the right illumination setup can often let you get away with nothing but a threshold binarization.
- CrimpCity 5y agoSeconded. Learned this the hard way when I bit off more than I could chew aka I took on the sun.