Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts

Abstract

In 1986, Tanner and Mead [1] implemented an interesting constraint sat(cid:173) isfaction circuit for global motion sensing in a VLSI. We report here a new and improved a VLSI implementation that provides smooth optical flow as well as global motion in a two dimensional visual field. The com(cid:173) putation of optical flow is an ill-posed problem, which expresses itself as the aperture problem. However, the optical flow can be estimated by the use of regularization methods, in which additional constraints are intro(cid:173) duced in terms of a global energy functional that must be minimized . We show how the algorithmic constraints of Hom and Schunck [2] on com(cid:173) puting smooth optical flow can be mapped onto the physical constraints of an equivalent electronic network.