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Dive into the research topics where Brian Salomon is active.

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Featured researches published by Brian Salomon.


interactive 3d graphics and games | 2003

Interactive navigation in complex environments using path planning

Brian Salomon; Maxim Garber; Ming C. Lin; Dinesh Manocha

We present a novel approach for interactive navigation in complex 3D synthetic environments using path planning. Our algorithm precomputes a global roadmap of the environment by using a variant of randomized motion planning algorithm along with a reachability-based analysis. At runtime, our algorithm performs graph searching and automatically computes a collision-free and constrained path between two user specified locations. It also enables local user-steered exploration, subject to motion constraints and integrates these capabilities in the control loop of 3D interaction. Our algorithm only requires the scene geometry, avatar orientation, and parameters relating the avatar size to the model size. The performance of the preprocessing algorithm grows as a linear function of the model size. We demonstrate its performance on two large environments: a power plant and a factory room.


ieee visualization | 2004

Quick-VDR: Interactive View-Dependent Rendering of Massive Models

Sung-Eui Yoon; Brian Salomon; Russell Gayle; Dinesh Manocha

We present a novel approach for interactive view-dependent rendering of massive models. Our algorithm combines view-dependent simplification, occlusion culling, and out-of-core rendering. We represent the model as a clustered hierarchy of progressive meshes (CHPM). We use the cluster hierarchy for coarse-grained selective refinement and progressive meshes for fine-grained local refinement. We present an out-of-core algorithm for computation of a CHPM that includes cluster decomposition, hierarchy generation, and simplification. We make use of novel cluster dependencies in preprocess to generate crack-free, drastic simplifications at runtime. The clusters are used for occlusion culling and out-of-core rendering. We add a frame of latency to the rendering pipeline to fetch newly visible clusters from the disk and to avoid stalls. The CHPM reduces the refinement cost for view-dependent rendering by more than an order of magnitude as compared to a vertex hierarchy. We have implemented our algorithm on a desktop PC. We can render massive CAD, isosurface, and scanned models, consisting of tens or a few hundreds of millions of triangles at 10-35 frames per second with little loss in image quality.


IEEE Transactions on Visualization and Computer Graphics | 2005

Quick-VDR: out-of-core view-dependent rendering of gigantic models

Sung-Eui Yoon; Brian Salomon; Russell Gayle; Dinesh Manocha

We present a novel approach for interactive view-dependent rendering of massive models. Our algorithm combines view-dependent simplification, occlusion culling, and out-of-core rendering. We represent the model as a clustered hierarchy of progressive meshes (CHPM). We use the cluster hierarchy for coarse-grained selective refinement and progressive meshes for fine-grained local refinement. We present an out-of-core algorithm for computation of a CHPM that includes cluster decomposition, hierarchy generation, and simplification. We introduce novel cluster dependencies in the preprocess to generate crack-free, drastic simplifications at runtime. The clusters are used for LOD selection, occlusion culling, and out-of-core rendering. We add a frame of latency to the rendering pipeline to fetch newly visible clusters from the disk and avoid stalls. The CHPM reduces the refinement cost of view-dependent rendering by more than an order of magnitude as compared to a vertex hierarchy. We have implemented our algorithm on a desktop PC. We can render massive CAD, isosurface, and scanned models, consisting of tens or a few hundred million triangles at 15-35 frames per second with little loss in image quality.


symposium on geometry processing | 2004

Fast collision detection between massive models using dynamic simplification

Sung-Eui Yoon; Brian Salomon; Ming C. Lin; Dinesh Manocha

We present a novel approach for collision detection between large models composed of tens of millions of polygons. Each model is represented as a clustered hierarchy of progressive meshes (CHPM). The CHPM is a dual hierarchy of the original model: it serves both as a multiresolution representation of the original model, as well as a bounding volume hierarchy. We use the cluster hierarchy of a CHPM to perform coarse-grained selective refinement and the progressive meshes for fine-grained local refinement. We present a novel conservative error metric to perform collision queries based on the multiresolution representation. We use this error metric to perform dynamic simplification for collision detection. Our approach is conservative in that it may overestimate the set of colliding regions, but never misses any collisions. Furthermore, we are able to generate these hierarchies and perform collision queries using out-of-core techniques on all triangulated models. We have applied our algorithm to perform conservative collision detection between massive CAD and scanned models, consisting of millions of triangles at interactive rates on a commodity PC.


ieee visualization | 2003

Interactive view-dependent rendering with conservative occlusion culling in complex environments

Sung-Eui Yoon; Brian Salomon; Dinesh Manocha

This paper presents an algorithm combining view-dependent rendering and conservative occlusion culling for interactive display of complex environments. A vertex hierarchy of the entire scene is decomposed into a cluster hierarchy through a novel clustering and partitioning algorithm. The cluster hierarchy is then used for view-frustum and occlusion culling. Using hardware accelerated occlusion queries and frame-to-frame coherence, a potentially visible set of clusters is computed. An active vertex front and face list is computed from the visible clusters and rendered using vertex arrays. The integrated algorithm has been implemented on a Pentium IV PC with a NVIDIA GeForce 4 graphics card and applied in two complex environments composed of millions of triangles. The resulting system can render these environments at interactive rates with little loss in image quality and minimal popping artifacts.


international conference on computer graphics and interactive techniques | 2004

Quick-VDR: interactive view-dependent rendering of massive models

Sung-Eui Yoon; Brian Salomon; Russell Gayle; Dinesh Manocha

We present a novel approach for interactive view-dependent rendering of massive models. Our algorithm combines view-dependent simplification, occlusion culling, and out-of-core rendering. We represent the model as a clustered hierarchy of progressive meshes (CHPM). We use the cluster hierarchy for coarse-grained selective refinement and progressive meshes for fine-grained local refinement. We present an out-of-core algorithm for computation of a CHPM that includes cluster decomposition, hierarchy generation, and simplification. We make use of novel cluster dependencies in the preprocess to generate crack-free, drastic simplifications at runtime. The clusters are used for occlusion culling and out-of-core rendering. We add a frame of latency to the rendering pipeline to fetch newly visible clusters from the disk and to avoid stalls. The CHPM reduces the refinement cost for view-dependent rendering by more than an order of magnitude as compared to a vertex hierarchy. We have implemented our algorithm on a desktop PC. We can render massive CAD, isosurface, and scanned models, consisting of tens or a few hundreds of millions of triangles at 10−35 frames per second with little loss in image quality.


international conference on e-learning and games | 2006

SKIT: a computer-assisted sketch instruction tool

Greg Coombe; Brian Salomon

In a visual world, the ability to sketch is an important asset for communicating complex ideas. However, sketching is a frustrating task for many people, and most never progress beyond a rudimentary skill level. In this paper we present SKIT, a computer-assisted sketch instruction tool. SKIT attempts to teach beginning students one of the important skills of sketching, the ability to perceive effectively. It is based on traditional art instruction techniques, which break the complex task of drawing into smaller tasks. These sub-tasks are combined into a final drawing, which can be then rendered using several different NPR styles. We also present preliminary results from people who have used SKIT.


Archive | 2002

Fast and Simple Occlusion Culling Using Hardware-based Depth Queries

Brian Salomon; Karl Hillesland; Anselmo Lastra; Dinesh Manocha


Archive | 2004

Accelerating Line of Sight Computation Using Graphics Processing Units

Brian Salomon; Naga K. Govindaraju; Avneesh Sud; Russell Gayle; Ming C. Lin; Dinesh Manocha; Brett Butler; Maria Bauer; Angel Rodriguez; Latika Eifert; Audrey Rubel; Michael Macedonia


Archive | 2006

Accelerating Route Planning and Collision Detection for Computer Generated Forces Using GPUs

David Tuft; Russell Gayle; Brian Salomon; Naga K. Govindaraju; Ming C. Lin; Dinesh Manocha; Maria Bauer; Angel Rodriguez; Michael Macedonia

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Dinesh Manocha

University of North Carolina at Chapel Hill

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Russell Gayle

University of North Carolina at Chapel Hill

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Ming C. Lin

University of North Carolina at Chapel Hill

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David Tuft

University of North Carolina at Chapel Hill

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Greg Coombe

University of North Carolina at Chapel Hill

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Anselmo Lastra

University of North Carolina at Chapel Hill

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Avneesh Sud

University of North Carolina at Chapel Hill

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