Motion Estimation and Segmentation Using a Recurrent Mixture-of-Experts Architecture
Yair Weiss and Edward H. Adelson
Proceedings of IEEE workshop on Neural Nets for Signal Processing V, pp. 293-303 (1995).
Estimating motion in scenes containing multiple motions remains a difficult problem for computer vision. Here we
describe a novel recurrent network architecture which solves this problem by simultaneously estimating motion and
segmenting the scene. The network is comprised of locally connected units which carry out simple calculations in
parallel. We present simulation results illustrating the successful motion estimation and rapid convergence of the
network on real images sequences.