Feature-based 3D morphing based on geometrically constrained spherical parameterization

Athanasiadis, Theodoros; Fudos, Ioannis; Nikou, Christophoros; Stamati, Vasiliki

doi:10.1016/j.cagd.2011.09.004

Cited by 16 publications

(5 citation statements)

References 21 publications

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“…On the 3D convex hull, the disturbance regions (DRs) of the face are identified as those exhibiting strong concavity intensities, as depicted as brighter areas in the concavity intensity map, and they are removed prior to the subsequent phase (i.e., see the bottom-right box), which also include the fusion of both modalities [12,13]. To ensure that the DRs are homogeneous and are strongly connected closures [7,10], a second stage of SymRG is also implemented.…”

Section: Methodsmentioning

confidence: 99%

Disturbance-Region Removal on Landmark-less Registration of Craniofacial Images Acquired by CBCT and 3D Photography

Wan¹,

Lo²,

Chang³

2021

IJETAE

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Superimposition of cranio-maxillofacial images acquired from cone-beam computed tomography (CBCT) and facial images acquired from three-dimensional photography (3D photography) can assist in diagnosis and surgical planning. Conventional approaches individually identified prominent facial landmarks on both modalities, respectively and assessed their correspondence. Considering, however, variation of facial expressions or drastic feature distortion when the face or head was imaged at different timing, landmark registration can become challenging. This paper proposes a disturbance-region removal (DRR) procedure to improve the efficacy of registration. The disturbance regions (DRs) are defined as those exhibiting strong responses in the concavity intensity maps that are computed from the facial surface mesh. Following this identification process for the DRs, an adapted symmetric region growing algorithm is used to form the connected DRs that are to be removed prior to superimposition of both modalities. The results show a twenty-eight percent better match of overall correspondence of the facial fiducial markers. Instead of being the registration guides in conventional approaches, in this study the fiducial markers are employed as only a means to assess the performance of registration

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Section: Methodsmentioning

confidence: 99%

Disturbance-Region Removal on Landmark-less Registration of Craniofacial Images Acquired by CBCT and 3D Photography

Wan¹,

Lo²,

Chang³

2021

IJETAE

View full text Add to dashboard Cite

show abstract

“…Lui et al [16,25] developed a method for landmark-constrained spherical parameterizations. In [26], Athanasiadis et al proposed a feature-preserving spherical parameterization method based on geometrically constrained optimization. In [27], Wang et al developed an as-rigid-as-possible method for spherical parameterization.…”

Section: Related Workmentioning

confidence: 99%

Fast spherical quasiconformal parameterization of genus-$0$ closed surfaces with application to adaptive remeshing

Choi

Man

Lui

2016

Geometry, Imaging and Computing

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Surface parameterization plays a fundamental role in many science and engineering problems. In particular, as genus-0 closed surfaces are topologically equivalent to a sphere, many spherical parameterization methods have been developed over the past few decades. However, in practice, mapping a genus-0 closed surface onto a sphere may result in a large distortion due to their geometric difference. In this work, we propose a new framework for computing ellipsoidal conformal and quasi-conformal parameterizations of genus-0 closed surfaces, in which the target parameter domain is an ellipsoid instead of a sphere. By combining simple conformal transformations with different types of quasi-conformal mappings, we can easily achieve a large variety of ellipsoidal parameterizations with their bijectivity guaranteed by quasi-conformal theory. Numerical experiments are presented to demonstrate the effectiveness of the proposed framework.

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“…Friedel et al [17] employed an energy minimization to generate spherical representations and achieved about 14K triangles/minute. Athanasiadis et al [32] presented a feature-based parameterization method and achieved about 1.1K triangles/minute. Aigerman [8] presented a parameterization method for surface property mapping and achieved about 3.5K triangles/minute.…”

Section: Performancementioning

confidence: 99%

Fast mapping and morphing for genus-zero meshes with cross spherical parameterization

Peng

Timalsena

2016

Computers & Graphics

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a b s t r a c tWe introduce an efficient approach to establish surface correspondences between genus-zero triangle meshes and animate a morph between them. We employ the concept of mesh simplification and refinement to progressively parameterize meshes using a novel kernel sampling algorithm. Our two-step feature alignment method optimizes the distribution of vertices in a parametric domain. A new mesh is generated after merging mesh topologies, and it represents the shapes of all input meshes and their transitions in-between. Our approach merges topological structures rather than mapping surface properties. Complex meshes with tens of thousands of vertices can be parameterized and merged in a few minutes. The advantages of our approach are demonstrated through 3D morphing applications. Comparing to existing approaches, our solution advances in performance while maintaining high-quality parameterization and morphing.Published by Elsevier Ltd.1

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Feature-based 3D morphing based on geometrically constrained spherical parameterization

Cited by 16 publications

References 21 publications

Disturbance-Region Removal on Landmark-less Registration of Craniofacial Images Acquired by CBCT and 3D Photography

Disturbance-Region Removal on Landmark-less Registration of Craniofacial Images Acquired by CBCT and 3D Photography

Fast spherical quasiconformal parameterization of genus-$0$ closed surfaces with application to adaptive remeshing

Fast mapping and morphing for genus-zero meshes with cross spherical parameterization

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