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Interactive collision detection for deformable models using streaming AABBs.

Xinyu Zhang1, Young J Kim

  • 1Department of Computer Science and Engineering, Ewha Womans University, Seoul, Korea. zhangxy@ewha.ac.kr

IEEE Transactions on Visualization and Computer Graphics
|January 16, 2007
PubMed
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This study introduces a fast, accurate collision detection algorithm for deforming objects using a streaming model. It achieves high frame rates by employing graphics processors for parallel collision checks and CPUs for detailed intersection tests.

Area of Science:

  • Computer Graphics
  • Computational Geometry
  • Parallel Computing

Background:

  • Collision detection is crucial for realistic simulations of deformable objects.
  • Existing methods often struggle with performance bottlenecks when dealing with severe deformations.
  • Streaming computational models offer a potential solution for high-throughput data processing.

Purpose of the Study:

  • To develop an interactive and accurate collision detection algorithm for deformable, polygonal objects.
  • To leverage the streaming computational model for efficient, massively-parallel collision detection.
  • To achieve high performance rates for complex, deforming models.

Main Methods:

  • Utilized a streaming computational model with axis-aligned bounding boxes (AABBs) for initial overlap detection.

Related Experiment Videos

  • Implemented massively-parallel pairwise overlap tests on graphics processing units (GPUs).
  • Employed a novel streaming algorithm for runtime geometric updates and a hierarchical en/decoding strategy for efficient result retrieval.
  • Performed primitive-level intersection checks on central processing units (CPUs) for overlapped AABBs.

    • Main Results:

    • The algorithm detects all pairwise primitive-level intersections between severely deforming models at interactive rates (30-100 FPS).
    • Achieved approximately three times performance improvement over the CULLIDE algorithm.
    • Demonstrated about two times improvement compared to a software-based AABB culling algorithm.
    • Successfully handled models with complexities ranging from 15K to 50K triangles under various deformations.

    Conclusions:

    • The proposed streaming collision detection algorithm offers significant performance gains for deformable objects.
    • The approach effectively overcomes performance stalls associated with traditional indexing mechanisms.
    • This method provides a robust and efficient solution for real-time collision detection in complex simulations.