In this paper, we discuss the parallelization of a computer vision applicatio- n for dense fluid motion estimation using OpenMP. The application uses a recent algorithm based on energy-based motion estimator for predicting and analyzing the motion in image sequences showing fluid phenomenon. Standard techniques from computer vision are not well adapted for such images because of the great deal of spatial and temporal distortions in luminance patterns. The multiresolution multigrid framework of the application renders it amenable to parallelization after appropriate changes to the algorithm. We discuss why OpenMP is a suitable alternative to the conventional message passing model and compare it with other models based on various aspects. The results obtained on a SMP machine from different parallelization strategies are demonstrated and compared.