For the segmentation and robust tracking of the cardiac left ventricle (LV) in MRI sequences, an optimized algorithm is presented; it is based on the active contour framework. To use the active contours model (ACM) (Kass, M. et al., Int. J. Comput. Vision, vol.1, p.321-31, 1998) to estimate cardiac motion, a new concept of generalized fuzzy gradient vector flow (GFGVF) is presented and compared with the classical gradient vector flow (GVF) (Chenyang Xu and Prince, J.L., "Gradient Vector Flow Deformable Models", Academic Press, 2000; Chung-Chu Leung and Wufan Chen, Proc. IEEE ICIP Conf., 2003). Then, a modified ACM is proposed for motion tracking, which is based on two new external forces: one is the GFGVF field; the other is the relativity of the optical flow field (OFF) on the predictive contour. For robust tracking of the outline of interest, a set of motion equations is presented to describe two correlative updating steps. Also, given some prior terms and likelihood one, the motion state of each point can be found by the maximum a posteriori probability (MAP).