Log in or register to post comments

Role of the image border?

April 10, 2011 - 4:07pm #1

A lot of the other CV based AR approaches that I'm familiar w/ rely on a distinct border region to the target / marker. QCAR's image tracking seems to be able to handle 'borderless' images pretty well, provided that there's adequate contrast and differentiation w/ the backdrop. But does the tracking algorithm make any assumptions about the border region of the image? What are best practices concerning the continuity and geometry of the border?

Re: Role of the image border?

April 16, 2011 - 12:39pm #5
Quote:

Feel free to send targets to

if you feel they should have worked well but didn't.

The false positives that I've encountered so far are predictable, when you recognize how the tracking operates. If you variegate the image a bit, by using a complex border or islands in the grid, they can perform well. It's just pure grids that are an issue.

Re: Role of the image border?

April 11, 2011 - 6:36pm #4

That's right, repeating patterns won't track well in general, the tracker can't distinguish one section of the pattern from another. The features should be somewhat random and noisy, but still distributed across the target.

Feel free to send targets to

if you feel they should have worked well but didn't. We'd be happy to review.

- Kim

Re: Role of the image border?

April 11, 2011 - 4:20pm #3

Interesting. Thanks.

Quote:

Just make sure that the portion of the image the user will focus on has a nice, even distribution of feature points.

Yes, but not too regular it seems. I've gotten false positives from the TMS on grid patterns, for instance. They'll rate a 5 but are never recognized.

Re: Role of the image border?

April 11, 2011 - 8:44am #2

The outermost border is not actually used in tracking, instead what matters is the distribution of features across the target as a whole. It is certainly possible to create non-rectangular targets where the features are concentrated in a portion of the rectangular image (e.g. a circular target). Note that these targets might get a lower score from the TMS, but experimentation should reveal whether the target performs to your needs. Just make sure that the portion of the image the user will focus on has a nice, even distribution of feature points. You can click on any target in the TMS to see the location of feature points across the target.

- Kim

Log in or register to post comments