Conference Paper

Bounded normal trees for reduced deformations of triangulated surfaces

DOI: 10.1145/1599470.1599480 Conference: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA 2009, New Orleans, Louisiana, USA, August 1-2, 2009
Source: DBLP


Several reduced deformation models in computer animation, such as linear blend skinning, point-based animation, embedding in finite element meshes, cage-based deformation, or subdivision surfaces, define surface vertex positions through convex combination of a rather small set of linear transformations. In this paper, we present an algorithm for computing tight normal bounds for a surface patch with an arbitrary number of triangles, with a cost linear in the number of governor linear transformations. This algorithm for normal bound computation constitutes the key element of the Bounded Normal Tree (BN-Tree), a novel culling data structure for hierarchical self-collision detection. In situations with sparse self-contact, normal-based culling can be performed with a small output-sensitive cost, regardless of the number of triangles in the surface.

Download full-text


Available from: Sara C. Schvartzman
  • [Show abstract] [Hide abstract]
    ABSTRACT: We propose a novel efficient deforming filter culling method for continuous collision detection (CCD) problem performed by dimension reduction in subspace. We present a fast linear filter (1D reduced filter) considering relative motion between primitives. We also provide a conservative and fast planar filter test (2D reduced filter) for self-collision feature pairs considering relative motion between vertex and edge. Filter test in subspace removes large amount of false positives and elementary tests with low cost, and improve the overall performance of collision query. We demonstrate our approach and compare it with previous alternatives in kinds of dynamic scenes. Combined with our linear and planar reduced filter, we observe a magnitude of speed improvement on elementary tests (over 2x) compared against previous ones. Our method keeps stable performance for simulations with large step time.
    No preview · Conference Paper · Jan 2010
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Skinning is a simple yet popular deformation technique combining compact storage with efficient hardware accelerated rendering. While skinned meshes (such as virtual characters) are traditionally created by artists, previous work proposes algorithms to construct skinning automatically from a given vertex animation. However, these methods typically perform well only for a certain class of input sequences and often require long pre-processing times. We present an algorithm based on iterative coordinate descent optimization which handles arbitrary animations and produces more accurate approximations than previous techniques, while using only standard linear skinning without any modifications or extensions. To overcome the computational complexity associated with the iterative optimization, we work in a suitable linear subspace (obtained by quick approximate dimensionality reduction) and take advantage of the typically very sparse vertex weights. As a result, our method requires about one or two orders of magnitude less pre-processing time than previous methods.
    Full-text · Article · Jun 2010 · Computer Graphics Forum
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Collision detection is a problem that has often been addressed efficiently with the use of hierarchical culling data structures. In the subproblem of self-collision detection for triangle meshes, however, such hierarchical data structures lose much of their power, because triangles adjacent to each other cannot be distinguished from actually colliding ones unless individually tested. Shape regularity of surface patches, described in terms of orientation and contour conditions, was proposed long ago as a culling criterion for hierarchical self-collision detection. However, to date, algorithms based on shape regularity had to trade conservativeness for efficiency, because there was no known algorithm for efficiently performing 2D contour self-intersection tests. In this paper, we introduce a star-contour criterion that is amenable to hierarchical computations. Together with a thorough analysis of the tree traversal process in hierarchical self-collision detection, it has led us to novel hierarchical data structures and algorithms for efficient yet conservative self-collision detection. We demonstrate the application of our algorithm to several example animations, and we show that it consistently outperforms other approaches.
    Full-text · Article · Jul 2010 · ACM Transactions on Graphics
Show more