Methods cooperation for multiresolution motion estimation

For a medical application, we are interested in an estimation of optical flow on a patient's face, particularly around the eyes. Among the methods of optical flow estimation, gradient estimation and block matching are the main methods. However, the gradient-based approach can only be applied for small displacements (one or two pixels). Gener- ally, the process of block matching leads to good results only if the searching strategy is judiciously selected. Our approach is based on a Markov random field model, combined with an algorithm of block match- ing in a multiresolution scheme. The multiresolution approach allows de- tection of a large range of speeds. The large displacements are detected on coarse scales and small displacements are detected successively on finer scales in a coarse to fine strategy. The Markov random fields allow the initialization and control of motion estimation across all scales. The tracking of motion is achieved by a block matching algorithm. This method gives the optical flow, whatever the amplitude of motion is, if pertaining to the range defined by the multiresolution approach. The re- sults clearly show the complement of Markov random field estimation and block matching across the scales. © 2002 Society of Photo-Optical Instru-