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3D reconstruction from 2D images with hierarchical continuous simplices

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Abstract

This paper presents an effective framework for the reconstruction of volumetric data from a sequence of 2D images. The 2D images are first aligned to generate an initial 3D volume, followed by the creation of a tetrahedral domain using the Carver algorithm. The resulting tetrahedralization preserves both the geometry and topology of the original dataset. Then a solid model is reconstructed using simplex splines with fitting and faring procedures. The reconstructed heterogenous volumetric model can be quantitatively analyzed and easily visualized. Our experiments demonstrated that our approach can achieve high accuracy in the data reconstruction. The novel techniques and algorithms proposed in this paper can be applied to reconstruct a heterogeneous solid model with complex geometry and topology from other visual data.

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  1. Department of Computer Science, Wayne State University, 5143 Cass Avenue, 431 State Hall, Detroit, MI, 48202, USA

    Yunhao Tan, Jing Hua & Ming Dong

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  1. Yunhao Tan
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  2. Jing Hua
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  3. Ming Dong
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Correspondence to Jing Hua.

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Tan, Y., Hua, J. & Dong, M. 3D reconstruction from 2D images with hierarchical continuous simplices. Visual Comput 23, 905–914 (2007). https://doi.org/10.1007/s00371-007-0157-0

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