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用于 3D 微笑面部模型配准的可靠参考区域:姿势微笑与自然微笑表情。

Reliable Reference Areas for 3D Smiling Facial Model Alignment: Posed vs Natural Smile Expressions.

出版信息

Int J Prosthodont. 2024 Aug 23;37(4):469-476. doi: 10.11607/ijp.8364.

Abstract

PURPOSE

To evaluate the reliability of various reference areas for digital alignment between 3D resting and smiling facial models.

MATERIALS AND METHODS

3D posed and natural smiling faces of 33 adults were registered to the respective neutral faces, using six matching strategies with different reference matching surfaces: nose (N), nose + central forehead (NFc), nose + whole forehead (NFw), nose + chin (NC), nose + central forehead + chin (NFcC), and nose + whole forehead + chin (NFwC). The positional discrepancies of the registered images were measured at the left and right pupil centers.

RESULTS

Two-way ANOVA and post hoc multiple pairwise t test with Bonferroni correction (α = .05) were used to evaluate the measurements. As a result, the use of larger reference areas increases the trueness of image-matching, whereas there was no statistically significant difference between the matching strategies within the same smiling type. Meanwhile, the image registration of posed smiles resulted in fewer positional disparities than the natural smiles with significant differences observed for the registration using the NC and NFcC surface-based matching areas at the right pupil (P = .030 and .026, respectively).

CONCLUSIONS

The findings of this study suggest that the reference surface areas and smiling types have some impact on the accuracy of 3D smiling facial image alignments. Large and evenly distributed matching surfaces are recommended for posed smiles, whereas caution should be taken when using the chin area as a reference surface for matching natural smile facial images.

摘要

目的

评估 3D 静止和微笑面部模型之间数字配准的各种参考区域的可靠性。

材料和方法

将 33 名成年人的 3D 摆拍和自然微笑面部图像与各自的中性面部图像进行配准,使用六种具有不同参考匹配面的匹配策略:鼻(N)、鼻+中央额头(NFc)、鼻+整个额头(NFw)、鼻+下巴(NC)、鼻+中央额头+下巴(NFcC)和鼻+整个额头+下巴(NFwC)。在左右瞳孔中心测量注册图像的位置差异。

结果

使用双向方差分析和事后多重配对 t 检验(Bonferroni 校正,α=0.05)来评估测量结果。结果表明,使用更大的参考区域可以提高图像匹配的准确性,而在同一微笑类型内的匹配策略之间没有统计学上的显著差异。同时,与自然微笑相比,摆拍微笑的图像注册导致的位置差异较小,在使用基于 NC 和 NFcC 表面的匹配区域进行右瞳孔注册时,差异具有统计学意义(P=0.030 和 0.026)。

结论

本研究的结果表明,参考面区域和微笑类型对 3D 微笑面部图像配准的准确性有一定影响。对于摆拍微笑,建议使用大而均匀分布的匹配面,而在使用下巴区域作为匹配自然微笑面部图像的参考面时则需要谨慎。

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