Assisted articulation of closed polygonal models

Teichmann, Marek; Teller, Seth

doi:10.1145/280953.282217

Cited by 39 publications

(21 citation statements)

References 2 publications

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“…A few approaches to skeleton extraction can be found in the literature. In 1998, Teichmann and Teller [38] extracted a skeleton by simplifying the Voronoi skeleton with user assistance. Liu et al in the year 2003 [26], used repulsive force fields to find a skeleton.…”

Section: -D Character Simulationmentioning

confidence: 99%

Senescence: An Age-Based Character Simulation Framework

Rajasekaran¹,

Adamo-Villani²

2015

2015 19th International Conference on Information Visualisation

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The paper presents the development and initial validation of the Senescence character framework, a simulation tool that can be used for rigging muscle deformer-based humanoid characters, with support for age. The senescence framework allows the user to rig any bipedal 3D character and manipulate skeleton and muscle parameters in order to render the age of the character realistically. The framework was developed using Python, Maya Embedded Language and PyQt. A study with 100 subjects was conducted to determine whether participants were able to perceive the age of the characters simulated with the Senescence framework. Findings show that while subjects were able to perceive age differences, they were not able to identify the age of the simulated characters with high level of accuracy. Results also show that subjects with animation expertise were able to identify the age of the characters more accurately than subjects without animation experience.

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Section: -D Character Simulationmentioning

confidence: 99%

Senescence: An Age-Based Character Simulation Framework

Rajasekaran¹,

Adamo-Villani²

2015

2015 19th International Conference on Information Visualisation

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“…The extracted segmentation is not necessarily an exact simplification of the shape, but allows to animate the model. Teichmann et al [16] first use the MAT for retrieving the skeleton of animation. From any closed polygonal mesh, they extract a simplified and cleaned MAT with manual intervention to select the main joints on this MAT.…”

Section: Introductionmentioning

confidence: 99%

“…Mixing geometric algorithms tends to increase the robustness and some of the presented approaches are quite successful in providing rough skeletons for simple shapes [16,18,10]. One of these recent approaches [18] provides sufficiently clean skeletons for animation, by connecting "domain control points" obtained using geometry shrinking with radial basis functions.…”

Section: Introductionmentioning

confidence: 99%

Knowledge-based extraction of control skeletons for animation

Delias

Moccozet

Magnenat‐Thalmann

et al. 2007

IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07)

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In this paper we propose a method for the automatic extraction and annotation of the animation control skeleton of virtual humans, which relies on an a-priori knowledge of the human anatomy. The method is based on a segmentation of the virtual human shape into semantically meaningful features, like arms or legs, and on an automatic location and labeling of joints of the control skeleton. The method is particularly relevant for computer animation where the process still largely relies on manual tasks, and especially for virtual characters built on real scanned data. Several examples will show the results obtained with our approach.

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“…Informally, it is the set of all points that have more than one closest point on the shape. The medial axis provides a compact representation of the shapes which has been used in a number of applications including image processing [22], computer vision [9], [23], solid modeling [14], [20], [27], [28], mesh generation [25], [26], motion planning [19] and many others [21], [29]. The shapes in this paper are surfaces embedded in 3D.…”

mentioning

confidence: 99%

“…For polyhedral input Etzion and Rappoport [17] suggest an approximation method based on octree subdivisions of space. Another scheme considered by many uses a set of sample points on the shape and then approximates the medial axis with the Voronoi diagram of these points [4]- [6], [11], [25], [29].…”

mentioning

confidence: 99%

Approximating the Medial Axis from the Voronoi Diagram with a Convergence Guarantee

2003

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The medial axis of a surface in 3D is the closure of all points that have two or more closest points on the surface. It is an essential geometric structure in a number of applications involving 3D geometric shapes. Since exact computation of the medial axis is difficult in general, efforts continue to improve their approximations. Voronoi diagrams turn out to be useful for this approximation. Although it is known that Voronoi vertices for a sample of points from a curve in 2D approximate its medial axis, a similar result does not hold in 3D. Recently, it has been discovered that only a subset of Voronoi vertices converge to the medial axis as sample density approaches infinity. However, most applications need a nondiscrete approximation as opposed to a discrete one. To date no known algorithm can compute this approximation straight from the Voronoi diagram with a guarantee of convergence. We present such an algorithm and its convergence analysis in this paper. One salient feature of the algorithm is that it is scale and density independent. Experimental results corroborate our theoretical claims.

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Assisted articulation of closed polygonal models

Cited by 39 publications

References 2 publications

Senescence: An Age-Based Character Simulation Framework

Senescence: An Age-Based Character Simulation Framework

Knowledge-based extraction of control skeletons for animation

Approximating the Medial Axis from the Voronoi Diagram with a Convergence Guarantee

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