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This paper proposes a nonlinear regression model to predict soft tissue deformation after maxillofacial surgery. The feature which served as input in the model is extracted with finite element model (FEM). The output in the model is the facial deformation calculated from the preoperative and postoperative 3D data. After finding the relevance between feature(More)
In this paper, we proposed a new 3D object retrieval method based on the visual keywords. In our method, the visual keywords are generated from the clusters of Relative Angle Context Distribution, which provides a statistical shape context that captures local shape characters and is also rotational and scale invariant. We also adopt the term frequency model(More)
Characteristic view is an effective way to represent a 3D object through a set of distinct projections from different view aspects. In this paper, we proposed techniques for automatic characteristic views generations by clustering views of the object from multiple view aspect. By considering the resulting clusters as View Topics that describe a set of(More)
Facial soft tissue deformation following osteotomy is associated with the corresponding biomechanical characteristics of bone and soft tissues. However, none of the methods devised to predict soft tissue deformation after osteotomy incorporates population-based statistical data. The aim of this study is to establish a statistical model to describe the(More)