• Title/Summary/Keyword: Hierarchical spline

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Study on the Local Refinement in Spline Finite Element Method by Using Hierarchical B-spline (계층적 B-스플라인을 이용한 스플라인 유한요소법의 국부 세분화에 관한 연구)

  • Hah, Zoo-Hwan;Kim, Hyun-Jung;Youn, Sung-Kie
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.8
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    • pp.1007-1013
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    • 2010
  • A new local refinement scheme for spline finite element method has been proposed; this scheme involves the use of hierarchical B-spline. NURBS has been widely used in CAD; however, the local refinement of NURBS is difficult due to its tensor-product property. In this study, we attempted to use hierarchical B-splines as local refinement strategy in spline FEM. The regions of high gradients are overlapped by hierarchically-created local meshes. Knot vectors and control points in local meshes are extracted from global meshes, and they are refined using specific schemes. Proper compatibility conditions are imposed between global and local meshes. The effectiveness of the proposed method is verified on the basis of numerical results. Further, it is shown that by using a proposed local refinement scheme, the accuracy of the solution can be improved and it could be higher than that of the solution of a conventional spline FEM with relatively lower degrees of freedom.

Multilevel Editing for Hierarchical B-spline Curves using Rotation Minimizing Frames (RMF을 이용한 계층적 B-spline 곡선의 다단계 편집기법)

  • Zhang, Ci;Yoon, Seung-Hyun;Lee, Ji-Eun
    • Journal of the Korea Computer Graphics Society
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    • v.16 no.4
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    • pp.41-50
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    • 2010
  • We present a new technique for multilevel editing of hierarchical B-spline curves. At each level, control points of a displacement function are expressed in the rotation minimizing frames (RMFs) [1] which are computed on nodal points of the curve at previous level. When the curve is edited at previous level, the corresponding RMFs are updated and the control points of the displacement function at current level are applied to the new RMFs, which maintains the relative details of the curve at current level to those of previous level. We demonstrate the effectiveness and robustness of the proposed technique using several experimental results.

Bayesian Curve-Fitting in Semiparametric Small Area Models with Measurement Errors

  • Hwang, Jinseub;Kim, Dal Ho
    • Communications for Statistical Applications and Methods
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    • v.22 no.4
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    • pp.349-359
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    • 2015
  • We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

Curve Reconstruction from Oriented Points Using Hierarchical ZP-Splines (계층적 ZP-스플라인을 이용한 곡선 복구 기법)

  • Kim, Hyunjun;Kim, Minho
    • Journal of the Korea Computer Graphics Society
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    • v.22 no.5
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    • pp.1-16
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    • 2016
  • In this paper, we propose and efficient curve reconstruction method based on the classical least-square fitting scheme. Specifically, given planar sample points equipped with normals, we reconstruct the objective curve as the zero set of a hierarchical implicit ZP(Zwart-Powell)-spline that can recover large holes of dataset without loosing the fine details. As regularizers, we adopted two: a Tikhonov regularizer to reduce the singularity of the linear system and a discrete Laplacian operator to smooth out the isocurves. Benchmark tests with quantitative measurements are done and our method shows much better quality than polynomial methods. Compared with the hierarchical bi-quadratic spline for datasets with holes, our method results in compatible quality but with less than 90% computational overhead.

Efficient Rolling Shutter Distortion Removal using Hierarchical Block-based Motion Estimation

  • Lee, Donggeun;Choi, Kang-Sun
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.4
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    • pp.205-211
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    • 2014
  • This paper reports an efficient algorithm for accurate rolling shutter distortion removal. A hierarchical global motion estimation approach for a group of blocks reduces the level of computation by three orders of magnitude. In addition, the motion of each scanline is determined accurately by averaging two candidates obtained through cubic spline interpolation. The experimental results show that the proposed method produces accurate motion information with significant computation reduction and corrects the rolling shutter distortion effectively.

Semiparametric Bayesian Estimation under Structural Measurement Error Model

  • Hwang, Jin-Seub;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • v.17 no.4
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    • pp.551-560
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    • 2010
  • This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

Semiparametric Bayesian estimation under functional measurement error model

  • Hwang, Jin-Seub;Kim, Dal-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.379-385
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    • 2010
  • This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

Smooth Path Generation using Hexagonal Cell Representation (육각형 격자를 사용한 부드러운 경로생성)

  • Jung, Dong-Won
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.12
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    • pp.1124-1132
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    • 2011
  • This paper deals with smooth path generation using B-spline for fixed-wing unmanned aerial vehicles manuevering in 2D environment. Hexagonal cell representation is employed to model the 2D environment, which features increased connectivity among cells over square cell representation. Subsequently, hexagonal cell representation enables smoother path generation based on a discrete sequence of path from the path planner. In addition, we present an on-line path smoothing algorithm incorporating B-spline path templates. The path templates are computed off-line by taking into account all possible path sequences within finite horizon. During on-line implementation, the B-spline curves from the templates are stitched together repeatedly to come up with a reference trajectory for UAVs. This method is an effective way of generating smooth path with reduced on-line computation requirement, hence it can be implemented on a small low-cost autopilot that has limited computational resources.

3D Model Compression For Collaborative Design

  • Liu, Jun;Wang, Qifu;Huang, Zhengdong;Chen, Liping;Liu, Yunhua
    • International Journal of CAD/CAM
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    • v.7 no.1
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    • pp.1-10
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    • 2007
  • The compression of CAD models is a key technology for realizing Internet-based collaborative product development because big model sizes often prohibit us to achieve a rapid product information transmission. Although there exist some algorithms for compressing discrete CAD models, original precise CAD models are focused on in this paper. Here, the characteristics of hierarchical structures in CAD models and the distribution of their redundant data are exploited for developing a novel data encoding method. In the method, different encoding rules are applied to different types of data. Geometric data is a major concern for reducing model sizes. For geometric data, the control points of B-spline curves and surfaces are compressed with the second-order predictions in a local coordinate system. Based on analysis to the distortion induced by quantization, an efficient method for computation of the distortion is provided. The results indicate that the data size of CAD models can be decreased efficiently after compressed with the proposed method.

3D Animation Authoring Tool Based On Whole Body IK and Motion Editing

  • Ju, Woo-Suk;Im, Choong-Jae
    • Journal of Korea Multimedia Society
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    • v.11 no.6
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    • pp.869-874
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    • 2008
  • The work of creating character motion needs the higher professional technology and sense and the creating work of realistic and natural motion possess the most part of production term. In this paper we introduce the easy and convenient 3D animation authoring tool which makes the motion based on whole-body inverse kinematics and motion editing function. The proposed 3D animation authoring tool uses the forward kinematics using quaternion and whole-body inverse kinematics to determine the rotation and displacement of skeleton. Also, it provides the motion editing function using multi-level B-spline with quasi-interpolant. By using the proposed tool, we can make 3D animation easily and conveniently.

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