Efficiently Computing and Updating Triangle Strips for Real-Time

Abstract

Triangle strips are a widely used hardware-supported data-structure to compactly represent and efficiently render polygonal meshes. In this paper, we survey the efficient generation of triangle strips as well as their variants. We present efficient algorithms for partitioning polygonal meshes into triangle strips. Triangle strips have traditionally used a buffer size of two vertices. In this paper, we also study the impact of larger buffer sizes and various queuing disciplines on the effectiveness of triangle strips. View-dependent simplification has emerged as a powerful tool for graphics acceleration in visualization of complex environments. However, in a view-dependent framework the triangle mesh connectivity changes at every frame making it difficult to use triangle strips. In this paper, we present a novel data-structure, Skip Strip, that efficiently maintains triangle strips during such view-dependent changes. A Skip Strip stores the vertex hierarchy nodes in a skip-list-like manner with path compression. We anticipate that Skip Strips will provide a road-map to combine rendering acceleration techniques for static datasets, typical of retained-mode graphics applications, with those for dynamic datasets found in immediate-mode applications.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA448090

Entities

People

  • Amitabh Varshney
  • Aravind Kalaiah
  • Elvir Azanli
  • Francine Evans
  • Jihad El-sana
  • Steven Skiena

Organizations

  • Stony Brook University

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Collapse
  • Computations
  • Computer Programs
  • Computer Science
  • Computers
  • Cost Models
  • Costs
  • Demographic Cohorts
  • Geometry
  • Hierarchies
  • Lists (Data Structures)
  • Mathematics
  • Polygons
  • Sequences
  • Triangles
  • Triangulation

Fields of Study

  • Computer science

Readers

  • Graph Algorithms and Convex Optimization.
  • Microwave Engineering.
  • Parallel and Distributed Computing.