We address the problem of non-rigid motion and correspondence estimation in 3D images in the absense of prior domain information. A generic framework is utilized in which a solution is approached by hypothesizing correspondence and evaluting the motion models constructed under each hypothesis. We present and evaluate experimentally five algorithms that can be used in this approach. Our experiments were carried out on synthetic and real data with ground truth correspondence information.
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