  This article introduces the structure flow field; a flow field that can
provide high-speed robo-centric motion information for motion control of highly
dynamic robotic devices and autonomous vehicles. Structure flow is the angular
3D velocity of the scene at a given pixel. We show that structure flow posses
an elegant evolution model in the form of a Partial Differential Equation (PDE)
that enables us to create dense flow predictions forward in time. We exploit
this structure to design a predictor-update algorithm to compute structure flow
in real time using image and depth measurements. The prediction stage takes the
previous estimate of the structure flow and propagates it forward in time using
a numerical implementation of the structure flow PDE. The predicted flow is
then updated using new image and depth data. The algorithm runs up to 600 Hz on
a Desktop GPU machine for 512x512 images with flow values up to 8 pixels. We
provide ground truth validation on high-speed synthetic image sequences as well
as results on real-life video on driving scenarios.
