It became apparent, even in the early works of Schunck that the task of optical flow estimation has to be carried out in conjunction with the task of motion segmentation (i.e. motion boundary detection). This fact has motivated the development of a novel model-based algorithm which is able to segment the optical flow field in an image into homogeneous regions which are consistent with a linear affine flow model. Furthermore, to ensure robustness in the presence of noise, this region-growing process is implemented within the hierarchical framework of a spatial lowpass pyramid. The results of applying this algorithm to the problem of estimating 3-D motion and structure in monocular image sequences are presented.