There are already good libraries for object tracking in 2D images and the additional features of project tango would likely add only marginal improvement in performance(of existing functions) for major overhauls of the library to support a small set of evolving hardware.
How do you think project tango could improve on existing object recognition & tracking?
With a 3d model of the object to be tracked, and knowledge of the motion and pose of the camera, one could predict what the next image of the tracked object 'should' look like. If the next image is different than predicted, it could be assumed that the tracked object has moved from its prior position. And the actual new 3D image could indicate the tracked object's vectors. That certainly has uses in navigating a live environment.
But that sounds like the sort of solution a self driving car might use. And that would be a valuable piece of tech worth keeping away from competitors despite its value to the community.
This is all just speculation. I have no first hand knowledge.