You haven't specified but if the observation noise is independent of the model noise then I think you should first combine the Y estimates with simple observation variance weighted mean as specified here:

http://en.wikipedia.org/wiki/Weighted_mean#Dealing_with_variance

after that apply kalman filter as if it is a univariate model. As a result you will have a lower observation noise hence a better estimate of x.

Multivariate exponential smoothing and Kalman filter equivalence
I am running a iOS project using the isgl3d framework for showing pod files.

I have a stylish car with 0.5 alpha windows, that I wish to render on a camera background, seeking some augmented reality goodness.

The alpha on the windows looks okay, but when I add the object, I notice that it renders the entire object transparently, where the windows are. Including interior of the car.

Like so (in example, keyboard can be seen through the dashboard, seats and so on. should be solid)



The car interior is a seperate object with alpha 1.0.

I would rather not show a "ghost car" in my project, but I haven't found a way around this.

Have anyone encountered the same issue, and eventually reached a solution ?
