Reconstruction of a Composite Surface by Reverse Engineering Techniques

Seo, Jin Young; Lee, H.-C.; Park, S.

doi:10.1007/s001700170126

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…Amenta et al [3] and Gavriliu [4] suggested two Voronoi-based surface reconstruction algorithms. Seol, Lee and Park [5] proposed a new approach to the reconstruction of a surface by generating triangular patches, comparing the triangular patches to the normal vector, categorizing the triangular patches, implementing an average planar face, and trimming all the edges. But the underlying assumptions of the proposed method are that most of the parts are composed of basic surfaces and many parts consist of analytically-basic surfaces, such as planes, cylinders, cones and spheres.…”

Section: Related Workmentioning

confidence: 99%

An adaptive mesh model for 3D reconstruction from unorganized data points

Yang

Xiong

2005

Int J Adv Manuf Technol

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Reconstructing exact topology mesh from data points is one of the most important tasks in the fields of industrial CAD/CAE/CAM, computational vision and reverse engineering. In this paper, a deflation algorithm that integrates an adaptive mesh and physical constraint model is presented for the 3D reconstruction of geometric-closed shape (genus 0) from unorganized data points. First, an initial mesh is formed using the Delaunay algorithm. Second, an asymptotic deforming performance is accomplished to deflate initial mesh towards the local concave boundary step-by-step. In this phase, a physical constraint model of coupled particle systems based on particle dynamics and Newtonian law of motion is constructed, and the model dynamically controls mesh deformation as a behavior constraint. To guarantee that the resultant mesh is homeomorphous to the original surface of data points, a continuously deforming mechanism, visibility cone and collision-detecting criterions are designed. At last, experimental results in reverse engineering which supports the usefulness of this method for reconstruction.

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Section: Related Workmentioning

confidence: 99%

An adaptive mesh model for 3D reconstruction from unorganized data points

Yang

Xiong

2005

Int J Adv Manuf Technol

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“…RMM is used to construct a model according to point cloud data (Jones et al , 1995; Seo et al , 2001; Huang and Menq, 2003; Wang, Chang and Yuen, 2003; Andreetto et al , 2004; Ke et al , 2006; Li et al , 2011; Wang et al , 2012). This modeling concept combines wireframe modeling and surface modeling in essence.…”

Section: Introductionmentioning

confidence: 99%

A mixed human body modeling method based on 3D body scanning for clothing industry

Liu

Wang

Zhu

et al. 2017

IJCST

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Purpose The purpose of this paper is to propose a relatively simple and rapid method to create a digital human model (DHM) to serve clothing industry. Design/methodology/approach Human body’s point cloud is divided into hands, foots, head and torso. Then forward modeling method is used to model hands and foots, photo modeling method is used to model head and reverse modeling method is used to model torso. After that, hands, foots, head and torso are integrated together to get a static avatar. Next, virtual skeleton is bound to the avatar. Finally, a lifelike digital human body model is created by the mixed modeling method (MMM). Findings In allusion to the defect of the three-dimension original data of human body, this paper presented an MMM, with which we can get a realistic digital human body model with accurate body dimensions. The DHM can well meet the needs of fashion industry. Practical implications The DHM, which is got by the MMM, can be well applied in the field of virtual try on, virtual fashion design, virtual fashion show and so on. Originality/value The originality of the paper lies in the integration of forward modeling, reverse modeling and photo modeling to present a novel method of human body modeling.

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