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Model-Based Human Teeth Shape Recovery from a Single Optical Image with Unknown Illumination

机译:从具有未知照明的单个光学图像中恢复基于模型的人牙齿形状

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Several existing 3D systems for dental applications rely on obtaining an intermediate solid model of the jaw (cast or teeth imprints) from which the 3D information can be captured. In this paper, we propose a model-based shape-from-shading (SFS) approach which allows for the construction of plausible human jaw models in vivo, without ionizing radiation, using fewer sample points in order to reduce the cost and intrusiveness of acquiring models of patients teeth/jaws over time. The inherent relation between the photometric information and the underlying 3D shape is formulated as a statistical model where the effect of illumination is modeled using Spherical Harmonics (SH) and the partial least square (PLS) approach is deployed to carry out the estimation of dense 3D shapes. Moreover, shape and texture alignment is accomplished using a proposed definition of anatomical jaw landmarks which can be automatically detected. Vis-a-vis dental applications, the results demonstrate a significant increase in accuracy in favor of the proposed approach. In particular, our approach is able to recover geometrical details of tooth occlusal surface as well as mouth floor and ceiling as compared to SFS-based approaches.
机译:现有的几种用于牙科应用的3D系统都依赖于获取颌的中间实体模型(铸模或牙齿印记),从中可以捕获3D信息。在本文中,我们提出了一种基于模型的阴影形成(SFS)方法,该方法允许使用较少的采样点在体内构建合理的人类下颌模型,而无需电离辐射,从而降低了获取成本和侵入性随时间变化的患者牙齿/颌骨模型。将光度信息与基础3D形状之间的固有关系公式化为统计模型,其中使用球谐(SH)建模照明效果,并采用偏最小二乘(PLS)方法进行密集3D估计形状。此外,使用可以自动检测的解剖颌骨界标的建议定义来实现形状和纹理对齐。相对于牙科应用,结果证明了准确性的显着提高,有利于所提出的方法。特别是,与基于SFS的方法相比,我们的方法能够恢复牙齿咬合面以及口腔底部和顶部的几何细节。

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