In this paper, an efficient scheme for video object segmentation is proposed. The scheme is based on a multiresolution Gradient Vector Flow field (M-GVF) and a Motion Geometric Space (MGS) formulation. In particular the proposed scheme is initialized from an object approximation which can be provided either (a) automatically (unsupervised case) based on a depth map estimation method or (b) semi-automatically by user interaction. In the following, several feature points are estimated on the initial object contour (i.e. depth object) and an M-GVF adapted MGS is created to determine the direction that a feature point is allowed to move to. In this framework, each feature point moves onto its MGS in order to locate the contour of the physical video object. Experimental results are presented to indicate the reliable performance of the proposed scheme on real life stereoscopic and monocular video sequences.