Statistical analysis of three-dimensional optical flow separability in volumetric images

Three-dimensional (3D) motion analysis of dynamic body organs using volumetric images is of increasing interest in different computer vision applications. A number of methods for estimation of 3D optical flow in those images have been developed in recent years. However, theoretical limits of 3D optical flow-based motion estimation and segmentation are yet to be analysed. In this study, a statistical analysis of 3D optical flow is presented and the results are used to predict the separability of local 3D motions. Experimental results, using both synthetic and real images, demonstrate the applicability of the proposed analysis to predict the separability of two motions in terms of the parameters quantifying their relative motion and the scale of measurement noise.