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Predator Object Tracking Algorithm

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Re: Predator Object Tracking Algorithm

#21

Post by y0ghur7_xxx »

extension wrote: post #15
exit wrote: post #9

> Can Predator be used to stabilize and navigate a Quadcopter? > That is not straightforward. anyone know why not?

Probably because this is just 2D tracking rather than 3D mapping. But tracking can be applied to mapping, for example: http://www.robots.ox.ac.uk/~gk/PTAM/ So the question is, can predator be used to improve mapping? AFAIK, that would require a) automatically selecting trackable objects and b) tracking many of them simultaneously. That PTAM technique tracks thousands, but with tracking this reliable, you might get by…

"AFAIK, that would require a) automatically selecting trackable objects and b) tracking many of them simultaneously."

I'm not really sure I understood you, but this two problems are already solved. Hugin[1] for example has automatic control point generation for photo stitching. Were you talking about something else?

[1]http://hugin.sourceforge.net/releases/2010.4.0/en.shtml

Re: Predator Object Tracking Algorithm

#22

Post by extension »

ChuckMcM wrote: post #16

As this doesn't seem like an April fools joke (some of the papers were published last year :-)) its interesting to think about it in the context of what it might change. That being said I don't doubt for a minute that the university has locked up as much of the technology as possible in patents but that is another story. We can speculate about what it will be like in 20 years when people can do this without infringin…

Depending on how well the computational load can be reduced to hardware small systems could provide for head mounted tracking systems

He's clearly developing it on his laptop with a shitty webcam. That's why this is amazing. Screw robotic manufacturing, this is for my phone.

Re: Predator Object Tracking Algorithm

#23

Post by 6ren »

The key thing seems not to be the specific algorithm, but the idea of using images obtained during performance for training - an algorithm that can do that. An early prototype algorithm, with lots of room for tweaking - and there are likely radically different learning algorithms, as yet untried or undiscovered, that work better. It seems that in the past, performance images has been religiously separated from training image.

It reminds me of early approaches for robot walking, which tried to plan everything out, and more recent approaches of incorporating feedback - which turned out to be much simpler and work better. Sort of waterfall vs. agile.

It seems a tad unreliable (his "mouse pointer" was lost a few times while still on screen), but this is still a prototype. It's really impressive how the panda was tracked in 360 orientations - probably helped by the distinctive colouring.

New input devices (this, kinect, multi-touch) and applications that can really use them, may be a main source of disruptive innovation in computers for the next decade or two.

Re: Predator Object Tracking Algorithm

#24

Post by ChuckMcM »

jallmann wrote: post #14
d2 wrote: post #10

This is massively ground breaking. You'll get it if you've used motion tracking on several game interfaces and had to make perfectly white backgrounds with bright lights to make it work. This is incredibly accurate - really game changing stuff.

>This is massively ground breaking. Sounds like you're used to bad algorithms. I think there is a serious disconnect between the state of the art in computer vision and what's used in industry. The demo was cool, but the techniques are not that revolutionary. From a cursory glance through the papers, it is basically AdaBoost (for detection) and Lucas-Kanade (for tracking), with a few extensions. Not to discount the g…

Valid comment but its analogous to claiming peanutbutter cups aren't novel because peanut butter and chocolate were both well known. There is novelty in being able to synthesize new systems from known elements which frankly I don't believe gets quite the credit it deserves. But that is just me.

The point is of course that being broadly familiar with a number of things can help you put together a novel thing out of a previously unknown combination of those things.

Re: Predator Object Tracking Algorithm

#25

Post by masklinn »

pyrhho wrote: post #2

Bah! I was hoping to download the source (from here: http://info.ee.surrey.ac.uk/Personal/Z.Kalal/tld.html ) and check out his algorithm, but he requires you to email him with his project. If anyone knows how the algorithm works, or where it is described in detail, I'd love to read that! Absolutely amazing stuff!

He's published 4 papers on the subject (they're available at the bottom of the page) why not start there?

Re: Predator Object Tracking Algorithm

#26

Post by liuliu »

6ren wrote: post #23

The key thing seems not to be the specific algorithm, but the idea of using images obtained during performance for training - an algorithm that can do that. An early prototype algorithm, with lots of room for tweaking - and there are likely radically different learning algorithms, as yet untried or undiscovered, that work better. It seems that in the past, performance images has been religiously separated from traini…

Not to dismiss the importance, but the idea is used in developing Ensemble Tracking: http://www.merl.com/projects/ensemble-tracking/

Re: Predator Object Tracking Algorithm

#27

Post by donnyg107 »

Every time something like this comes out, I feel us taking a step away from "video camera mounted on a robot where the eyes should be" and a step toward real perception. I always wonder though, if a computer can one day recognize all different types of hands, could it draw a new one?

Re: Predator Object Tracking Algorithm

#28

Post by jhuckestein »

6ren wrote: post #23

The key thing seems not to be the specific algorithm, but the idea of using images obtained during performance for training - an algorithm that can do that. An early prototype algorithm, with lots of room for tweaking - and there are likely radically different learning algorithms, as yet untried or undiscovered, that work better. It seems that in the past, performance images has been religiously separated from traini…

The tracking was incredibly good. The first seconds of each example are a little off because the algorithm doesn't have ANY training data to work with. It's 100% ad-hoc.

The tracking improved during the mouse pointer example (which I found incredibly impressive). The point he was making during that example was that it learns the different scales/rotations of objects on the fly and tracking improves automatically.

Re: Predator Object Tracking Algorithm

#29

Post by [deleted] »

6ren wrote: post #23

The key thing seems not to be the specific algorithm, but the idea of using images obtained during performance for training - an algorithm that can do that. An early prototype algorithm, with lots of room for tweaking - and there are likely radically different learning algorithms, as yet untried or undiscovered, that work better. It seems that in the past, performance images has been religiously separated from traini…

[deleted]

Re: Predator Object Tracking Algorithm

#30

Post by sp332 »

extension wrote: post #12
sp332 wrote: post #4

With something like this we could have truly “Minority Report” style human-computer interface. Actually, the guy who invented the Minority Report interface commercialized it and has been selling it for years. Product website: http://oblong.com Edit better video: http://www.ted.com/talks/john_underkoffler_drive_3d_data_wit...

Predator doesn't need gloves

Well, he mentioned a "Minority Report"-style interface, and there it is. At least they could use cooler gloves: http://singularityhub.com/2010/05/28/mits-ridiculously-color... :)
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