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This demonstrates augmentation of a generic picture postcard with video in realtime. As opposed to using special image markers for tracking (as with ARToolKit) this form of augmentation can be applied to any complex image. The postcard is tracked using a standard webcam and The Artvertiser software.

Here's a video of this software working on street advertisements: vimeo.com/3464018

See theartvertiser.com for more details.

(NB: it appears a little slower than it is due to the fact I'm capturing it to disk using 3d screencapture software).

Credits

48 Likes

  • marcell mars 7 months ago
    awesome
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  • moka 5 months ago
    cool work. are there any documentations about the technique to track custom shapes/cards?

    Thanks!
  • Julian Oliver 5 months ago
    You can search around for algorithms on 'fast image tracking'. You can also look for a library that abstracts over OpenCV's pre-existing object detection or, depending on your needs, implement your own using OpenCV's example: see the 'find_obj.cpp' code in the samples directory of the latest distribution for a guide.

    I plan to release the source for this project as soon as the code is good and ready. Keep an eye on theartvertiser.com and/or julianoliver.com/blog for details about this!
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  • josekiamora 5 months ago
    just like Bryan Chung did using Proce55ing
    youtube.com/watch?v=FeTYvbcU2zQ
    youtube.com/watch?v=0DPMf529DIg
  • Julian Oliver 5 months ago
    Thanks for the links.

    It's not so similar really. Bryan Chung is using the widely popular ARToolKit tracker with 'fiducial markers' - in other words specially defined black and white images with a large black border - on which to composite video. The image in the first video he is using is the default marker shipped with the software, 'Hiro'.

    The video example I posted here uses any complex image: street advertising, a picture t-shirt or billboards being good examples of candidates. The technique is known as Natural Feature Tracking and doesn't require using pre-defined codes/markers for augmentation to be possible..

    Cheers!
  • josekiamora 5 months ago
    Thank you for the explaniton.I learned many technical terms from your reply.Yes your code and software is more complex and more successful but idea is the same,right?But anyway its really good.Selecting TED intro as sample video is another good point :)
    Cheers
    Erdem
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  • thesystemis plus 5 months ago
    love this and the idea of the project too !
    did you try bazar, or is this all homegrown?
    cvlab.epfl.ch/software/bazar/

    btw, theo and I used a homegrown technique here:
    vimeo.com/4336830

    finding corners based on curvature and using that data for the AR...
  • Julian Oliver 5 months ago
    The tracker part started out with OpenCV's own object detection tools (above comment). Later I found the 2d->3d homographic stuff in (OpenCV based) Bazar to be really clean and useful so I decided to go with this over my own (hairier) solutions.

    Overall though I've found Bazar to be too slow for AR, especially on a netbook target. The geometric calibration part needs a lot of careful attention to generate a good augmentation also. Since I've found several areas in which to optomise to bring it all up to ~25fps: beforehand it was ~10-15fps on a pretty powerful box..

    I'd reccommend just rolling your own solution around the OpenCV planar object detection code if your needs are simple. If you need all that homographic goodness then Bazar is the way to go!

    Cheers (and I like the card tricks ;)
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