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John Keyser

Bio: John Keyser is an academic researcher from Texas A&M University. The author has contributed to research in topics: Rendering (computer graphics) & Voronoi diagram. The author has an hindex of 28, co-authored 107 publications receiving 3168 citations. Previous affiliations of John Keyser include University of North Carolina at Chapel Hill & State University of New York System.


Papers
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Proceedings ArticleDOI
01 Jul 1999
TL;DR: A new approach for computing generalized 2D and 3D Voronoi diagrams using interpolation-based polygon rasterization hardware is presented and the application of this algorithm to fast motion planning in static and dynamic environments, selection in complex user-interfaces, and creation of dynamic mosaic effects is demonstrated.
Abstract: We present a new approach for computing generalized 2D and 3D Voronoi diagrams using interpolation-based polygon rasterization hardware. We compute a discrete Voronoi diagram by rendering a three dimensional distance mesh for each Voronoi site. The polygonal mesh is a bounded-error approximation of a (possibly) non-linear function of the distance between a site and a 2D planar grid of sample points. For each sample point, we compute the closest site and the distance to that site using polygon scan-conversion and the Z-buffer depth comparison. We construct distance meshes for points, line segments, polygons, polyhedra, curves, and curved surfaces in 2D and 3D. We generalize to weighted and farthest-site Voronoi diagrams, and present efficient techniques for computing the Voronoi boundaries, Voronoi neighbors, and the Delaunay triangulation of points. We also show how to adaptively refine the solution through a simple windowing operation. The algorithm has been implemented on SGI workstations and PCs using OpenGL, and applied to complex datasets. We demonstrate the application of our algorithm to fast motion planning in static and dynamic environments, selection in complex user-interfaces, and creation of dynamic mosaic effects. CR Categories: I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling; I.3.3 [Computer Graphics]: Picture/Image Generation. Additional

559 citations

Proceedings ArticleDOI
01 May 2000
TL;DR: A new approach for computing generalized 2D and 3D Voronoi diagrams using interpolation-based polygon rasterization hardware is presented and the application of this algorithm to fast motion planning in static and dynamic environments, selection in complex user-interfaces, and creation of dynamic mosaic effects is demonstrated.
Abstract: We present a new approach for computing generalized 2D and 3D Voronoi diagrams using interpolation-based polygon rasterization hardware. We compute a discrete Voronoi diagram by rendering a three dimensional distance mesh for each Voronoi site. The polygonal mesh is a bounded-error approximation of a (possibly) non-linear function of the distance between a site and a 2D planar grid of sample points. For each sample point, we compute the closest site and the distance to that site using polygon scan-conversion and the Z-buffer depth comparison. We construct distance meshes for points, line segments, polygons, polyhedra, curves, and curved surfaces in 2D and 3D. We generalize to weighted and farthest-site Voronoi diagrams, and present efficient techniques for computing the Voronoi boundaries, Voronoi neighbors, and the Delaunay triangulation of points. We also show how to adaptively refine the solution through a simple windowing operation. The algorithm has been implemented on SGI workstations and PCs using OpenGL, and applied to complex datasets. We demonstrate the application of our algorithm to fast motion planning in static and dynamic environments, selection in complex user-interfaces, and creation of dynamic mosaic effects. CR Categories: I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling; I.3.3 [Computer Graphics]: Picture/Image Generation. Additional

492 citations

Proceedings ArticleDOI
06 Jun 2006
TL;DR: An iterative approach that simultaneously generates a hierarchical shape decomposition and a corresponding set of multi-resolution skeletons and iterates until the quality of the skeleton becomes satisfactory.
Abstract: Shape decomposition and skeletonization share many common properties and applications. However, they are generally treated as independent computations. In this paper, we propose an iterative approach that simultaneously generates a hierarchical shape decomposition and a corresponding set of multi-resolution skeletons. In our method, a skeleton of a model is extracted from the components of its decomposition --- that is, both processes and the qualities of their results are interdependent. In particular, if the quality of the extracted skeleton does not meet some user specified criteria, then the model is decomposed into finer components and a new skeleton is extracted from these components. The process of simultaneous shape decomposition and skeletonization iterates until the quality of the skeleton becomes satisfactory. We provide evidence that the proposed framework is efficient and robust under perturbation and. deformation. We also demonstrate that our results can readily be used in problems including skeletal deformations and virtual reality navigation.

136 citations

Journal ArticleDOI
TL;DR: An accurate algorithm to compute the internal Voronoi diagram and medial axis of a 3-D polyhedron using exact arithmetic and exact representations for accurate computation of the medial axis is presented.

110 citations

Proceedings ArticleDOI
01 Jun 1999
TL;DR: In this paper, the internal Voronoi region and medial axis of a 3D polyhedron are computed using exact arithmetic and representations for accurate computation of the medial axis, where the sheets, seams, and junctions are represented as trimmed quadric surfaces, algebraic space curves and points with algebraic coordinates.
Abstract: We present an accurate and efficient algorithm to compute the internal Voronoi region and medial axis of a 3-D polyhedron. It uses exact arithmetic and representations for accurate computation of the medial axis. The sheets, seams, and junctions of the medial axis are represented as trimmed quadric surfaces, algebraic space curves, and points with algebraic coordinates, respectively. The algorithm works by recursively finding neighboring junctions along the seam curves. It uses spatial decomposition and linear programming to speed up the search step. We also present a new algorithm for analysis of the topology of an algebraic plane curve, which is the core of our medial axis algorithm. To speed up the computation, we have designed specialized algorithms for fast computation on implicit geometric structures. These include lazy evaluation based on multivariate Stiirm sequences, fast resultant computation, curve topology analysis, and floating-point filters. The algorithm has been implemented and we highlight its performance on a number of examples.

106 citations


Cited by
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Proceedings ArticleDOI
01 Aug 2001
TL;DR: A novel technique is proposed, called Topology Matching, in which similarity between polyhedral models is quickly, accurately, and automatically calculated by comparing Multiresolutional Reeb Graphs (MRGs), which operates well as a search key for 3D shape data sets.
Abstract: There is a growing need to be able to accurately and efficiently search visual data sets, and in particular, 3D shape data sets. This paper proposes a novel technique, called Topology Matching, in which similarity between polyhedral models is quickly, accurately, and automatically calculated by comparing Multiresolutional Reeb Graphs (MRGs). The MRG thus operates well as a search key for 3D shape data sets. In particular, the MRG represents the skeletal and topological structure of a 3D shape at various levels of resolution. The MRG is constructed using a continuous function on the 3D shape, which may preferably be a function of geodesic distance because this function is invariant to translation and rotation and is also robust against changes in connectivities caused by a mesh simplification or subdivision. The similarity calculation between 3D shapes is processed using a coarse-to-fine strategy while preserving the consistency of the graph structures, which results in establishing a correspondence between the parts of objects. The similarity calculation is fast and efficient because it is not necessary to determine the particular pose of a 3D shape, such as a rotation, in advance. Topology Matching is particularly useful for interactively searching for a 3D object because the results of the search fit human intuition well.

2,406 citations

Proceedings Article
01 Jan 1999

2,010 citations

Journal ArticleDOI
TL;DR: This report describes, summarize, and analyzes the latest research in mapping general‐purpose computation to graphics hardware.
Abstract: The rapid increase in the performance of graphics hardware, coupled with recent improvements in its programmability, have made graphics hardware a compelling platform for computationally demanding tasks in a wide variety of application domains. In this report, we describe, summarize, and analyze the latest research in mapping general-purpose computation to graphics hardware. We begin with the technical motivations that underlie general-purpose computation on graphics processors (GPGPU) and describe the hardware and software developments that have led to the recent interest in this field. We then aim the main body of this report at two separate audiences. First, we describe the techniques used in mapping general-purpose computation to graphics hardware. We believe these techniques will be generally useful for researchers who plan to develop the next generation of GPGPU algorithms and techniques. Second, we survey and categorize the latest developments in general-purpose application development on graphics hardware. This survey should be of particular interest to researchers who are interested in using the latest GPGPU applications in their systems of interest.

1,998 citations

Proceedings Article
01 Jan 2005
TL;DR: The techniques used in mapping general-purpose computation to graphics hardware will be generally useful for researchers who plan to develop the next generation of GPGPU algorithms and techniques.
Abstract: The rapid increase in the performance of graphics hardware, coupled with recent improvements in its programmability, have made graphics hardware a compelling platform for computationally demanding tasks in a wide variety of application domains. In this report, we describe, summarize, and analyze the latest research in mapping general-purpose computation to graphics hardware. We begin with the technical motivations that underlie general-purpose computation on graphics processors (GPGPU) and describe the hardware and software developments that have led to the recent interest in this field. We then aim the main body of this report at two separate audiences. First, we describe the techniques used in mapping general-purpose computation to graphics hardware. We believe these techniques will be generally useful for researchers who plan to develop the next generation of GPGPU algorithms and techniques. Second, we survey and categorize the latest developments in general-purpose application development on graphics hardware. This survey should be of particular interest to researchers who are interested in using the latest GPGPU applications in their systems of interest.

1,728 citations

Journal ArticleDOI
TL;DR: This highly successful textbook, widely regarded as the “bible of computer algebra”, gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems.
Abstract: Computer algebra systems are now ubiquitous in all areas of science and engineering. This highly successful textbook, widely regarded as the “bible of computer algebra”, gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems. Designed to accompany oneor two-semester courses for advanced undergraduate or graduate students in computer science or mathematics, its comprehensiveness and reliability has also made it an essential reference for professionals in the area. Special features include: detailed study of algorithms including time analysis; implementation reports on several topics; complete proofs of the mathematical underpinnings; and a wide variety of applications (among others, in chemistry, coding theory, cryptography, computational logic, and the design of calendars and musical scales). A great deal of historical information and illustration enlivens the text. In this third edition, errors have been corrected and much of the Fast Euclidean Algorithm chapter has been renovated.

937 citations