Implementation of an automatic semi-fluid motion analysis algorithm on a massively parallel computer

The implementation of a parallel algorithm for estimating non-rigid motion vectors using a semi-fluid motion model applied to time-varying satellite imagery is described. Deformable motion tracking of non-rigid biological objects and remotely-sensed objects, such as clouds, atmospheric aerosols and gases, polar sea ice or ocean currents, are important application domains for the semi-fluid motion analysis (SMA) algorithm. The focus of this paper is on the parallelization of the SMA algorithm for the MasPar MP-2 architecture. Implementation issues that were evaluated in order to make it feasible to explore dense semi-fluid motion estimates of rapid-scan time-varying geostationary satellite imagery of clouds and weather patterns are described. Cloud motion vectors from the SMA algorithm can be used to estimate the wind field that would be useful in a variety of meteorological applications. Comparisons between the parallel and sequential implementations of the SMA algorithm and with manual results are briefly discussed.