Snake-Based Boundary Search for Segmentation of 3D Polygonal Model

Ng, Kok-Why; Abdullah, Junaidi; Ng, Sew-Lai; Tong, Hau-Lee

doi:10.1007/978-981-13-6031-2_35

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…This section will discuss the potential problems while working on the 3D blending research work. The examples given in this section are our implemented interpolation of geometric model blending using the Laplacian-based contraction and Slinky-based segmentation method [33]- [34]. Due to limited paper length, readers may refer to the cited papers for more information on the contraction and segmentation methods.…”

Section: Analysis On the Potential Research Problems In 3d Blending Workmentioning

confidence: 99%

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Blending of three-dimensional geometric model shapes

Rahmat

et al. 2022

IJEECS

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Three-dimensional (3D) geometric model shapes blending method can create various in-between models from two inputs of models shapes. Though, many blended shapes are implausible due to different inputs of model type, inappropriate matching-parts, improper parts-segmentation, and non-tally number of segmentation parts. are crucial and should be taken into account. The objective of this paper is to study the strengths and weaknesses of some prominent shapes blending methods and the 3D reconstruction methods. An interpolated shape blending program using the Laplacian-based contraction and Slinky-based segmentation method is developed to illustrate the critical problems arise in the shape blending process. Output results are to be compared with some prominent existing methods and one will observe the potential research direction in the blending research work

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Section: Analysis On the Potential Research Problems In 3d Blending Workmentioning

confidence: 99%

“…Figure 2(b) shows the comparison of our proposed method to the existing seven prominent methods. The details of the seven methods are discussed in [33]. Accurate segmentation plays a very crucial role to ensure the correctness at the preliminary stage.…”

Section: Analysis On the Potential Research Problems In 3d Blending Workmentioning

confidence: 99%

Blending of three-dimensional geometric model shapes

Rahmat

et al. 2022

IJEECS

Self Cite

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“…根据顶点或面的几何特征定位分割区域的边界, 而不是分割区域本身. 采用基于轮廓的方法 [18] 自动搜索 2 个相连功能特征之间的边界. 通过求解拉普拉斯方程组和一种凹度敏感加权方法 [19]…”

Section: 相关工作unclassified

3D Mesh Segmentation Based on Energy Optimization

Gong¹,

He²,

Chen³

2021

J Comput-Aided Design Comput Graphics

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In order to improve the problems of over-segmentation, obvious zigzag segmentation lines, and too much human intervention in existing 3D mesh model segmentation methods, a segmentation method based on energy optimization and distinction was proposed. Firstly, it used two more robust features, i.e., energy and distinction, to improve the accuracy of the segmentation boundaries. Secondly, based on the energy, distinction, and concavity, the segmentation points were found; by using the adjacency of the points, the segmentation points sets were obtained; and the segmentation lines were obtained by refining the segmentation points sets based on the corrosion algorithm. Finally, closed segmentation lines were constructed based on the breadth-first search algorithm and the minimum energy principle. In addition, a Dijkstra type optimization method was provided to optimize the shape and position of the segmentation lines. Experiments on the Princeton segmentation benchmark were carried out, and comparisons with seven general segmentation methods under the Princeton Shape Benchmark were done. The most important index, called the Rand index, is 0.21 higher than the seven other methods in average, shows that the proposed method can effectively get more meaningful segmentation results.

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An End-to-End Segmentation Network for the Temporomandibular Joints CBCT Image based on 3D U-Net

Zhang

et al. 2020

2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

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Snake-Based Boundary Search for Segmentation of 3D Polygonal Model

Cited by 3 publications

References 13 publications

Blending of three-dimensional geometric model shapes

Blending of three-dimensional geometric model shapes

3D Mesh Segmentation Based on Energy Optimization

An End-to-End Segmentation Network for the Temporomandibular Joints CBCT Image based on 3D U-Net

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