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The patent on SIFT expired yesterday

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61–69 of 69 posts

Re: The patent on SIFT expired yesterday

#61

Is sift still relevant today?

As a computer vision practitioner, I would argue that SIFT is still very relevant today. In most real-world scenarios it seems to hold up as well or better than the deep learning approaches I've tried, and it is easier to implement and maintain. Failures are often easy to understand and mitigate. In practice I often end up using FAST or ORB features due to "good enough" accuracy but much faster processing rates, especially on embedded devices. Feature detection and matching is an area where "classical" computer vision is very much alive and well.

Re: The patent on SIFT expired yesterday

#63

Earlier quoted context omitted.

wait... the concept was to have video cameras on the ground point upward in a supermarket setting? Did anyone involved in this ever stop to think "what would a person wearing a skirt say to this?" It's not exactly the kind of thing you'd expect to be able to explain away with "oh no but we really don't use it for that" no?

A more charitable reading is that the cameras are at ground level and stay aimed at ground level. I got the impression he's not talking about the main basket of the shopping cart, but the storage right above the wheels where you might forget pet food or bulk paper goods.

okay, that might be my non-native English comprehension. I parsed "bottom of the basket" as the flat underside of the main part of the cart. And you'd have to point the cameras upwards to see that.

If it's horizontal, that's a different topic.

Re: The patent on SIFT expired yesterday

#64
post #15

There have been many better feature detectors introduced in the mix over the past fifteen years. This change won't make too big a difference for people in the CV community.

Mhhhhh, I'm a researcher in the field and I'd say it's a mostly inaccurate statement. The root-SIFT detectors and descriptors are still really good. If you try to match images in different conditions (day/night), then CNN based approaches are OK. Which one were you thinking about?

GMS feature matching trumps SIFT (and all other feature matchers) in just about every category including performance.

Re: The patent on SIFT expired yesterday

#65

Evolution Robotics (later acquired by iRobot) was the first licensee of this patent for robotics applications. It was very cutting edge for the time and allowed our robots the ability to recognize real world objects. Having the robot follow a book that you carried in front of it was trippy in 2002. Later we applied it to loss prevention in grocery retail with cameras at ground level watching under the cart. If we rec…

MobileVet, as an ex-Evolution Robotics person, I might have some media you're interested in (they might have come from you, if I'm guessing correctly who you are...).

Email me at jjwiseman@gmail.com.

Re: The patent on SIFT expired yesterday

#66

Does this mean that OpenCV will be able to now include SIFT in the “free” modules. Or are there more roadblocks before including it?

I really hope so. Including SIFT in OpenCV should be easy since they did have an implementation earlier, which they removed due to the licensing.

Re: The patent on SIFT expired yesterday

#67
post #48
post #40

Earlier quoted context omitted.

I'm not a lawyer, but as far as I know expired US patents enter the public domain. After their expiration the described invention can be freely used by anyone for any purpose [1]. So I think the answers to your questions are yes and no. [1] https://www.nolo.com/legal-encyclopedia/how-long-is-my-paten...

Perhaps there are still patents in other regions (?)

As others commented, the only countries where software patents work are the US and Japan. So it'd be just Japan that could have a patent in place? Don't know theh details, and IANAL.

OTOH, I'd really like the patent to be inactive, it'd allow me to work worry free in a lot of things that I've had an interest in.

Re: The patent on SIFT expired yesterday

#68

Earlier quoted context omitted.

A more charitable reading is that the cameras are at ground level and stay aimed at ground level. I got the impression he's not talking about the main basket of the shopping cart, but the storage right above the wheels where you might forget pet food or bulk paper goods.

okay, that might be my non-native English comprehension. I parsed "bottom of the basket" as the flat underside of the main part of the cart. And you'd have to point the cameras upwards to see that. If it's horizontal, that's a different topic.

I had the same impression upon first read. And from a programmers perspective of what the ideal conditions for such a software would be, I also thought of a ground placed camera, pointing upwards in a way in which id could see the basket an find items that were "forgotten" in it.
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