Automatic 3D skull reconstruction using invariant features

L. Ballerini, M. Calisti, S. Damas, O. Cordón, J. Santamaría
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Abstract

In this work we propose a new method to segment range images. It automatically extracts invariant features directly from point clouds. Points belonging to such features are used as the input to improve an evolutionary approach to 3D range image registration in forensic anthropology. We use such features in the automatic reconstruction of an accurate 3D model of the skull. Our reconstruction method includes a pre-alignment stage, that uses a subset of feature points, and a refinement stage. Results are presented over a set of instances of real problems.
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基于不变性特征的自动三维颅骨重建
本文提出了一种新的距离图像分割方法。它直接从点云中自动提取不变性特征。属于这些特征的点被用作输入,以改进法医人类学中三维距离图像配准的进化方法。我们使用这些特征来自动重建一个精确的颅骨3D模型。我们的重建方法包括一个使用特征点子集的预对齐阶段和一个细化阶段。结果是通过一组实际问题的实例提出的。
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