Adaptive-size physically-based models for nonrigid motion analysis

Huang, Wen‐Chen; Goldgof, Dmitry B.

doi:10.1109/cvpr.1992.223246

Cited by 21 publications

(6 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Deformable models, which come in many varieties, have been used to solve the problem in the physics-based modeling paradigm. These models involve the use of either fixed size [37], [50], [55], [56], [57] or adaptive size [51], [53], [58], [59], [60], [61] grids. The models with fixed grid size generally use a fewer number of degrees of freedom for representation at the cost of accuracy of the recovered shape.…”

Section: Rationalementioning

confidence: 99%

Dynamic modeling of butterfly subdivision surfaces

Mandal

Qin²,

Vemuri³

2000

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

ÐIn this paper, we develop integrated techniques that unify physics-based modeling with geometric subdivision methodology and present a scheme for dynamic manipulation of the smooth limit surface generated by the (modified) butterfly scheme using physics-based ªforceº tools. This procedure-based surface model obtained through butterfly subdivision does not have a closed-form analytic formulation (unlike other well-known spline-based models) and, hence, poses challenging problems to incorporate mass and damping distributions, internal deformation energy, forces, and other physical quantities required to develop a physics-based model. Our primary contributions to computer graphics and geometric modeling include: 1) a new hierarchical formulation for locally parameterizing the butterfly subdivision surface over its initial control polyhedron, 2) formulation of dynamic butterfly subdivision surface as a set of novel finite elements, and 3) approximation of this new type of finite elements by a collection of existing finite elements subject to implicit geometric constraints. Our new physics-based model can be sculpted directly by applying synthesized forces and its equilibrium is characterized by the minimum of a deformation energy subject to the imposed constraints. We demonstrate that this novel dynamic framework not only provides a direct and natural means of manipulating geometric shapes, but also facilitates hierarchical shape and nonrigid motion estimation from large range and volumetric data sets using very few degrees of freedom (control vertices that define the initial polyhedron).

show abstract

Section: Rationalementioning

confidence: 99%

Dynamic modeling of butterfly subdivision surfaces

Mandal

Qin²,

Vemuri³

2000

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

show abstract

“…Terzopoulos, Witkin, and Kass [3] create a membraneihin-plate elastic model relative to the spring forces to maintain the model flexible and stable for 3-D object reconstruction. Huang and Goidgof [6,7,8] built an adaptive-size meshes to reconstruct and analyze nonrigid motion objects. They formulate deformable superquadrics incorporating the global shape parameters with the local degrees of freedom of a spline.…”

Section: Introductionmentioning

confidence: 99%

<title>Nonrigid motion analysis using nonlinear finite element modeling</title>

Huang

Goldgof

1993

SPIE Proceedings

View full text Add to dashboard Cite

Finding corresponding points during nonrigid motion is a difficult but important problem. If the correspondence between all the points innonrigid motion can be determined, the complete information about the motion can be found. That requires the application of a specific constraint (similar to nonrigidity constraints utilized by rigid motion analysis algorithms). However, nonrigid motion has extremely varying nature (consider articulated motion V.5. motion of fluids). Hence, it is very unlikely that we can find a single nonrigidity assumption which can be utilized by all applications. Therefore, the idea is to utilize possible a priori knowledge to limit possible nonrigid behaviors. This a priori knowledge may be general or specific, local or global.In this paper, we consider the problem of tracking elastic objects with known material properties. That corresponds to utilization of specific a priori knowledge in nonrigid motion analysis. We propose the utilization of nonlinear finite element methods(FEM) for point correspondence recovery. We deal with range data, i.e. assume that surface points before and after motion are available from the sensing system. Nonlinear FEM not only allows for modeling of nonlinear material properties but also for large deformation between consecutive time frames (which are main limitations of widely utilized linear FEM). We propose a new algorithm for the point correspondence recovery in nonrigid motion using assumptions of known material properties and single (but not known) force applied to the object. Simulations and experimental results demonstrate the performance of the proposed algorithm. 0-8194-1280-5/931$6.0O Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/23/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

show abstract

“…In our experiments, we called the points where these forces were applied forced points. Huang [37] assigned the displacements of forced points instead of applying the forces to the object. This is an adaptation of the general inverse problem category used in nondestructive (electromagnetic, acoustic) testing [35].…”

Section: Nonlinear Finite Element Modelingmentioning

confidence: 99%

“…Furthermore, they develop techniques for adaptive hierarchical subdivision of adaptive meshes. Huang and Goldgof [18][19][20] built adaptive-size meshes to reconstruct and analyze nonrigid motion. In that approach, the mesh size increases or decreases dynamically during the surface reconstructing process to locate nodes near surface areas of interests (like high curvature points) and to optimize the fitting error.…”

Section: Previous Workmentioning

confidence: 99%

Efficient Nonlinear Finite Element Modeling of Nonrigid Objects via Optimization of Mesh Models

Tsap¹,

Goldgof²,

Sarkar³

et al. 1998

Computer Vision and Image Understanding

View full text Add to dashboard Cite

In this paper we propose a new general framework for the application of the nonlinear finite element method (FEM) to nonrigid motion analysis. We construct the models by integrating image data and prior knowledge, using well-established techniques from computer vision, structural mechanics, and computer-aided design (CAD). These techniques guide the process of optimization of mesh models.Linear FEM proved to be a successful physically based modeling tool in solving limited types of nonrigid motion problems. However, linear FEM cannot handle nonlinear materials or large deformations. Application of nonlinear FEM to nonrigid motion analysis has been restricted by difficulties with high computational complexity and noise sensitivity.We tackle the problems associated with nonlinear FEM by changing the parametric description of the object to allow easy automatic control of the model, using physically motivated analysis of the possible displacements to address the worst effects of the noise, applying mesh control strategies, and utilizing multiscale methods. The combination of these methods represents a new systematic approach to a class of nonrigid motion applications for which sufficiently precise and flexible FEM models can be built.The results from the skin elasticity experiments demonstrate the success of the proposed method. The model allows us to objectively detect the differences in elasticity between normal and abnormal skin. Our work demonstrates the possibility of accurate computation of point correspondences and force recovery from range image sequences containing nonrigid objects and large motion.

show abstract

Adaptive-size physically-based models for nonrigid motion analysis

Cited by 21 publications

References 7 publications

Dynamic modeling of butterfly subdivision surfaces

Dynamic modeling of butterfly subdivision surfaces

<title>Nonrigid motion analysis using nonlinear finite element modeling</title>

Efficient Nonlinear Finite Element Modeling of Nonrigid Objects via Optimization of Mesh Models

Contact Info

Product

Resources

About