3D mesh morphing based on a metamesh has fundamental limitations of complicated in-between meshes and no topology (connectivity) changes in a metamorphosis. This paper presents a novel approach for 3D mesh morphing, w...
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ISBN:
(纸本)0769517846;0769517854
3D mesh morphing based on a metamesh has fundamental limitations of complicated in-between meshes and no topology (connectivity) changes in a metamorphosis. This paper presents a novel approach for 3D mesh morphing, which is not based on a metamesh. The approach simultaneously interpolates the topology and geometry of input meshes. In our approach, an in-between mesh contains only the vertices from the source and target meshes. Since no additional vertices are introduced, the in-between meshes are much simpler than those generated by previous techniques.
We present a physically-inspired model of wax crayons, which synthesizes drawings from collections of user-specified strokes. Paper is represented by a height-field texture, and a crayon is modelled with a 2D mask tha...
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ISBN:
(纸本)0769520286
We present a physically-inspired model of wax crayons, which synthesizes drawings from collections of user-specified strokes. Paper is represented by a height-field texture, and a crayon is modelled with a 2D mask that evolves as it interacts with the paper. The amount of wax deposition is computed based on the crayon contact profile, contact force, and friction. Previously deposited wax is smeared by crayon action, based on wax softness and contact information. The distributed wax is rendered using a simplified Kubelka-Monk model, which approximates light transmittance and scattering effects.
We present a method for the adaptive reconstruction of a surface directly from an unorganized point cloud. The algorithm is based on an incrementally expanding Neural Network and the statistical analysis of its Learni...
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ISBN:
(纸本)0769520286
We present a method for the adaptive reconstruction of a surface directly from an unorganized point cloud. The algorithm is based on an incrementally expanding Neural Network and the statistical analysis of its Learning process. In particular, we make use of the simple observation that during the Learning process the normal of a vertex near a sharp edge or a high curvature area of the target space, statistically, will vary more than the normal of a vertex near a flat area. We use the information obtained from the study of these normal variations to steer the Learning process in an adaptive meshing application, producing meshes with more triangles near the high curvature areas. The same information is used in a feature detection application.
We formulate and apply spectral clustering to 3D mesh segmentation for the first time and report our preliminary findings. Given a set of mesh faces, an affinity matrix which encodes the likelihood of each pair of fac...
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ISBN:
(纸本)0769522343
We formulate and apply spectral clustering to 3D mesh segmentation for the first time and report our preliminary findings. Given a set of mesh faces, an affinity matrix which encodes the likelihood of each pair of faces belonging to the same group is first constructed. Spectral methods then use selected eigenvectors of the affinity matrix or its closely related graph Laplacian to obtain data representations that can be more easily clustered. We develop an algorithm that favors segmentation along concave regions, which is inspired by human perception. Our algorithm is theoretically sound, efficient, simple to implement, and can achieve high quality segmentation results on 3D meshes.
This paper presents a method that can convert a given 3D mesh into a flat-foldable model consisting of rigid panels. A previous work proposed a method to assist manual design of a single component of such flat-foldabl...
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This paper presents a method that can convert a given 3D mesh into a flat-foldable model consisting of rigid panels. A previous work proposed a method to assist manual design of a single component of such flat-foldable model, consisting of vertically-connected side panels as well as horizontal top and bottom panels. Our method semi-automatically generates a more complicated model that approximates the input mesh with multiple convex components. The user specifies the folding direction of each convex component and the fidelity of shape approximation. Given the user inputs, our method optimizes shapes and positions of panels of each convex component in order to make the whole model flat-foldable. The user can check a folding animation of the output model. We demonstrate the effectiveness of our method by fabricating physical paper prototypes of flat-foldable models.
In this paper, we first introduce an algorithm for estimating the visual contrast on a 3D mesh. We then perform a series of psychophysical experiments to study the effects of contrast sensitivity and contrast discrimi...
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In this paper, we first introduce an algorithm for estimating the visual contrast on a 3D mesh. We then perform a series of psychophysical experiments to study the effects of contrast sensitivity and contrast discrimination of the human visual system for the task of differentiating between two contrasts on a 3D mesh. The results of these experiments allow us to propose a perceptual model that is able to predict whether a change in local contrast on 3D mesh, induced by a local geometric distortion, is visible or not. Finally, we illustrate the utility of the proposed perceptual model in a number of applications: we compute the Just Noticeable Distortion (JND) profile for smooth-shaded 3D meshes and use the model to guide mesh processing algorithms.
Superpixels have been widely used as a preprocessing step in various computer vision tasks. Spatial compactness and color homogeneity are the two key factors determining the quality of the superpixel representation. I...
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Superpixels have been widely used as a preprocessing step in various computer vision tasks. Spatial compactness and color homogeneity are the two key factors determining the quality of the superpixel representation. In this paper, these two objectives are considered separately and anisotropic superpixels are generated to better adapt to local image content. We develop a unimodular Gaussian generative model to guide the color homogeneity within a superpixel by learning local pixel color variations. It turns out maximizing the log-likelihood of our generative model is equivalent to solving a Centroidal Voronoi Tessellation (CVT) problem. Moreover, we provide the theoretical guarantee that the CVT result is invariant to affine illumination change, which makes our anisotropic superpixel generation algorithm well suited for image/video analysis in varying illumination environment. The effectiveness of our method in image/video superpixel generation is demonstrated through the comparison with other state-of-the-art methods.
Volume visualization using isosurface extraction is a well-researched topic. Recent research demonstrated that even for unstructured grids peak performances of millions of tetrahedra per second can be achieved by expl...
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ISBN:
(纸本)0769522343
Volume visualization using isosurface extraction is a well-researched topic. Recent research demonstrated that even for unstructured grids peak performances of millions of tetrahedra per second can be achieved by exploiting the parallel processing capabilities of modem GPUs. In this paper we present a novel hardware-accelerated solution that further improves the extraction performance. In contrary to existing approaches, our technique explicitly extracts the isosurface geometry in a fragment program by rendering only a single screen-sized quadrilateral. The extracted geometry is directly written to an on-board graphics memory object allowing for direct rendering without further bus transfers. Additionally, the geometry can be manipulated by shader programs or read back to the application for further processing. Examples and application scenarios are given that can benefit from our approach.
We present a part-type segmentation method for articulated voxel-shapes based on curve skeletons. Shapes are considered to consist of several simpler, intersecting shapes. Our method is based on the junction rule : th...
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We present a part-type segmentation method for articulated voxel-shapes based on curve skeletons. Shapes are considered to consist of several simpler, intersecting shapes. Our method is based on the junction rule : the observation that two intersecting shapes generate an additional junction in their joined curve-skeleton near the place of intersection. For each curve-skeleton point, we construct a piece wise-geodesic loop on the shape surface. Starting from the junctions, we search along the curve skeleton for points whose associated loops make for suitable part cuts. The segmentations are robust to noise and discretization artifacts, because the curve skeletonization incorporates a single user-parameter to filter spurious curve-skeleton branches. Furthermore, segment borders are smooth and minimally twisting by construction. We demonstrate our method on several real-world examples and compare it to existing part-type segmentation method.
This paper presents several methods for shading meshes from scanned paint samples that represent dark to light transitions. Our techniques emphasize artistic control of brush stroke texture and color. We first demonst...
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ISBN:
(纸本)0769520286
This paper presents several methods for shading meshes from scanned paint samples that represent dark to light transitions. Our techniques emphasize artistic control of brush stroke texture and color. We first demonstrate how the texture of the paint sample can be separated from its color gradient. We demonstrate three methods, two real-time and one off-line, for producing rendered, shaded images from the texture samples. All three techniques use texture synthesis to generate additional paint samples. Finally, we develop metrics for evaluating how well each method achieves our goal in terms of texture similarity;shading correctness and temporal coherence.
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