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Role of the image border?

By Tyro on Wed, 06/20/2012 - 17:03
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?

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).

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. [/QUOTE] Yes, but not too regular it seems. I've gotten false positives from the TMS on grid patterns, for instance.

That's right, repeating patterns won't track well in general, the tracker can't distinguish one section of the pattern from another.

[QUOTE]Feel free to send targets to [email]qcar-support@qualcomm.com[/email] if you feel they should have worked well but didn't. [/QUOTE] The false positives that I've encountered so far are predictable, when you recognize how the tracking operates.