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A Corresponding Method of 3D Skull Feature Points Based on Voxel Models and Multi-Geometric Feature Constraint

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DOI: 10.23977/msmee.2018.72122


Yang Wen, Liu Xiaoning, Wang Kegang, Hu Jiabei, Zhu Fei, Geng Guohua

Corresponding Author

Liu Xiaoning


In the craniofacial reconstruction method based on statistical model, several feature points need to be calibrated on each skull. Due to the large number of feature points, the order of calibration is difficult to orderly, so it is necessary to carry out point correspondence to the calibrated feature points, and it is convenient to carry out subsequent statistical analysis. Therefore, a 3D skull correspondence algorithm based on voxel models and multi-geometric feature constraint is proposed in this paper. First, the skull model is unified into the Frankfurt coordinate system. According to the corresponding relationship between the reference skull and the corresponding set of skull points, the matching skull is deformed by TPS, and the skull is coarsely registered; Then, a voxel model of reference skull and skull to be matched is constructed to solve multi-geometric features of feature points set of the model; Finally, under the joint constraint of multi-geometric features, the best counterpart is achieved. Experimental results show that the proposed algorithm improves the accuracy and efficiency significantly.


3D skull, point correspondence, voxel models, thin plate spline, geometric feature constraint

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