Disparity flow depicts the 3D motion of a scene in disparity space of a given view and can be considered as view-dependent scene flow. The disparity flow map of a given view is a 2D array of 3D vectors that depicts the 3D motion observed at different pixel locations. Estimating 3D motion in form of disparity flow map limits all computations in the 2D image space and converts the 3D motion estimation problem into a 2D labeling problem. A novel algorithm is presented in this paper for disparity flow estimation using the orthogonal reliability-based dynamic programming technique. Experimental results using captured stereo sequences show that the new algorithm can generate dense and smooth 3D motion for dynamic scenes.