Non-rigid point set registration: recent trends and challenges - Artificial Intelligence Review

Non-rigid point set registration has been used in a wide range of computer vision applications such as human movement tracking, medical image analysis, three dimensional (3D) object reconstruction and is a very challenging task. It has two fundamental tasks. One is to find correspondences between two or more point sets and another is to transform a point set so that it aligns with other point sets. There has been significant progress in the past two decades in the non-rigid registration field but it still has major challenges and is an active research area in the computer vision and pattern recognition community. In this review, we present a survey of non-rigid point set registration.