3.9 Article

Computerized assembly of neurocranial fragments based on surface extrapolation

期刊

ANTHROPOLOGICAL SCIENCE
卷 121, 期 2, 页码 115-122

出版社

ANTHROPOLOGICAL SOC NIPPON
DOI: 10.1537/ase.130618

关键词

virtual reconstruction; Bezier surface; assemblage; fossil; computed tomography

资金

  1. Japanese Ministry of Education, Culture, Sports, Science and Technology
  2. Grants-in-Aid for Scientific Research [22101006] Funding Source: KAKEN

向作者/读者索取更多资源

Fossil crania are often fractured and fragmented due to compaction and diagenesis. To restore the antemortem appearance of a fossil cranium, it is necessary to correctly assemble the fragments into their original anatomical positions. In this study, we propose a concept for computerized reconstruction that employs surface extrapolation to aid the assembly of fossil neurocranial fragments. Specifically, we approximate the surface of each neurocranial fragment using a bicubic Bezier surface to extrapolate the surface and mathematically predict the shape of adjacent fragments. The positions and orientations of adjacent fragments were calculated by minimizing the fitting errors. To evaluate the usefulness of this concept, we virtually divided modern human and chimpanzee neurocrania into pieces and used the proposed method to reassemble the generated virtual fragments. The neurocranial fragments were smoothly and correctly assembled. Comparison of the results obtained using the proposed method and conventional manual assembly revealed that the proposed method delivered similar performance in terms of differences between the original and reassembled shapes. However, the accuracy of the reassembly was found to be worse in the chimpanzee case because the fragments were more curved than those for the human cranium. Although there are some methodological limitations, the proposed concept may be useful for development of digital reassembly of fossil neurocranial fragments.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.9
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据