ON PARALLEL IMPLEMENTATION OF HORN AND SCHUNCK MOTION ESTIMATION METHOD

Fella Charif, Noureddine Djedi, and Abderrazak Benchabane

Keywords

Motion estimation, Horn and Schunck method, Zhang neural network, realtime applications

Abstract

The aim of this study is to present a fast parallel implementation of the Horn and Schunck method using a new kind of recurrent neural network called discrete Zhang neural networks. This network is characterized by a few iterations to converge which make it very suitable for real-time motion estimation. To compute the optical flow, we propose to solve directly the system of equations utilizing the discrete Zhang neural networks for matrix inversion instead of the original iterative method. The simulation results for synthetic and real image sequences show that the proposed algorithm is faster than the Horn and Schunck method.

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