Thanks for the report, I've created an internal bug report for us to take a look at.

I recreated the Unity project with the steps you provided, and while I agree that objects off the center of the target experience a little more jitter, I didn't find that it was a serious problem. Note that tracking is always going to work better when you are focused squarely on the target. The result won't be as stable if you are capturing only a small segment of the target at a steep angle, which seems required to focus on an object floating this far off the target.

I would say this is a good AR design tip. Place your objects such that the user naturally focuses on the target, not in places that draws their attention away from the target.

Finally, could you let us know what device you are testing on?

- Kim

I am using Droid X with 2.2.1

I had the entire target in the camera, and was focused squarely on the target.

Did you notice how the scale change makes the jitter get worse?

Hi guys, we have the same issue with our game prototype. We want to use a small marker (business card size, 3.5" x 2") and while QCAR has no problem tracking it, objects on the periphery (we have a barbwire fence to keep players from wandering too far away) shake and jitter a lot.

Like cyjohnson above, this is a big deal for us...we have considered putting a damper on the camera to prevent it from jittering, but the tests we've done so far show it's not that simple, as it tends to rub out small natural movements which help create the sense of Augmented Reality.

Just wondering if any progress has been made in that direction...the competition (which shall remain nameless) does not display that issue on our iOS prototype. :-/

Cheers!

Hello,

Can you please post a video of the jitter you are seeing?

Thank you,

-Peter

No problem, I'll do this tomorrow. What's the best way to post videos here? Link to YouTube?

PS For what it's worth the jitter effect does not happen when using FrameMarkers...

You can observe the effects of the offset error, in relation to the camera's perspective, but developing a model like this one.

This is simply an arrangement of individual cylinders, aligned as rods, running perpendicular and parallel to the target face. The panels are transparent cubes with a grid texture. By aligning the rods and grids, you can observe, the magnitude of error for various offset distances and angles, for a given perspective.

What you'll notice is that lateral offset is more stable than vertical offset and that this instability tends to increase as you approach a perpendicular perspective. Vertically offset models above the origin will actually bend away from the camera center as you approach a perpendicular alignment.

Some other observations are that the error propagation appears to be linear and uniform for all points at a given distance (i.e. the error is of the same magnitude in the same direction and grows linearly). And the models actually are jittering, they're not simply oscillating between two points. The magnitude of each jump appears to be consistent, for a given distance, but the direction of the error appears to be random. I haven't analyzed these values to determine if they truly are random.

So pruning these values may be a more effective approach than trying to correct them.