Abstract
This paper presents a novel, powerful reconstruction algorithm that can recover correct shape geometry as well as its unknown topology from arbitrarily complicated volumetric datasets. The algorithm starts from a simple seed model (of genus zero) that can be initialized automatically without user intervention. The deformable behavior of the model is then governed by a locally defined objective function associated with each vertex of the model. Through the numerical computation of function optimization, the algorithm can adaptively subdivide the model geometry, automatically detect self-collision of the model, properly modify its topology (because of the occurrence of self-collision), continuously evolve the model towards the object boundary, and reduce fitting error and improve fitting quality via global subdivision.
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Duan, Y., Qin, H. (2001). Extracting Boundary Surface of Arbitrary Topology from Volumetric Datasets. In: Mueller, K., Kaufman, A.E. (eds) Volume Graphics 2001. Eurographics. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6756-4_16
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DOI: https://doi.org/10.1007/978-3-7091-6756-4_16
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83737-5
Online ISBN: 978-3-7091-6756-4
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