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Fast and Accurate 3D Reconstruction of Dental Models

机译:快速准确的牙科模型3D重建

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There are three main processes in 3D reconstruction: point cloud generation, point cloud registration, and point cloud merging. A merging algorithm is necessary to fuse range images obtained from multiple directions in order to achieve a complete model of a single surface. In merging phase, most low cost RGB-d sensors use volumetric range image processing (VRIP) to fuse 3D data in realtime. However, VRIP isn't suitable for 3D measurement of dental models because the quality of 3D data from its low resolution depth image cannot satisfy high precision of dental CAD systems. To achieve greater details, We suggest to introduce a new idea, so-called angle truncation, into VRIP to fuse 3D data quickly and retain fine details simultaneously. We also discuss various distance metric and blending functions in scanning dental impressions. Finally, dental impression model is scanned to compare the accuracy and the speed of our method, the original VRIP, and Pois-son surface reconstruction which is often preferred in 3d reconstruction. The results show that the method's accuracy is improved to the original VRIP and the time efficiency is enhanced compared to the Poisson surface reconstruction.
机译:3D重建包含三个主要过程:点云生成,点云注册和点云合并。需要一种合并算法来融合从多个方向获得的距离图像,以实现单个表面的完整模型。在合并阶段,大多数低成本RGB-d传感器使用体积范围图像处理(VRIP)实时融合3D数据。但是,VRIP不适合用于牙科模型的3D测量,因为来自其低分辨率深度图像的3D数据的质量无法满足牙科CAD系统的高精度。为了获得更多细节,我们建议在VRIP中引入一种称为“角度截断”的新想法,以快速融合3D数据并同时保留精细细节。我们还将讨论扫描牙齿印模时的各种距离度量和混合功能。最后,扫描牙齿印模模型以比较我们的方法,原始VRIP和Pois-son表面重建的准确性和速度,这在3d重建中通常是首选的。结果表明,与Poisson曲面重建相比,该方法的精度比原始VRIP有所提高,并且时间效率得到了提高。

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