Model-based multiresolution motion estimation in noisy images

Abstract It is argued that accurate optical flow can only be determined if problems such as local motion ambiguity, motion segmentation, and occlusion detection are simultaneously addressed. To meet this requirement, a new multiresolution region-growing algorithm is proposed. This algorithm consists of a region-growing process which is able to segment the flow field in an image into homogeneous regions which are consistent with a linear affine flow model. To ensure stability and 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 both natural and synthetic image sequences are presented.