An accurate method for voxelizing polygon meshes
VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Fast computation of generalized Voronoi diagrams using graphics hardware
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A complete distance field representation
Proceedings of the conference on Visualization '01
Fast 3D triangle-box overlap testing
Journal of Graphics Tools
Efficient max-norm distance computation and reliable voxelization
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Efficient algorithms for solving static hamilton-jacobi equations
Efficient algorithms for solving static hamilton-jacobi equations
Signed Distance Computation Using the Angle Weighted Pseudonormal
IEEE Transactions on Visualization and Computer Graphics
Signed Distance Transform Using Graphics Hardware
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Interactive 3D distance field computation using linear factorization
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
Hierarchical RLE level set: A compact and versatile deformable surface representation
ACM Transactions on Graphics (TOG)
3D Distance Fields: A Survey of Techniques and Applications
IEEE Transactions on Visualization and Computer Graphics
GI '07 Proceedings of Graphics Interface 2007
Out-of-core and compressed level set methods
ACM Transactions on Graphics (TOG)
VDB: High-resolution sparse volumes with dynamic topology
ACM Transactions on Graphics (TOG)
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The signed distance field for a polygonal model is a useful representation that facilitates efficient computation in many visualization and geometric processing tasks. Often it is more effective to build a local distance field only within a narrow band around the surface that holds local geometric information for the model. In this paper, we present a novel technique to construct a volumetric local signed distance field of a polygonal model. To compute the local field efficiently, exactly those cells that cross the polygonal surface are found first through a new voxelization method, building a list of intersecting triangles for each boundary cell. After their neighboring cells are classified, the triangle lists are exploited to compute the local signed distance field with minimized voxeltotriangle distance computations. While several efficient methods for computing the distance field, particularly those harnessing the graphics processing unit's (GPU's) processing power, have recently been proposed, we focus on a CPU-based technique, intended to deal flexibly with large polygonal models and high-resolution grids that are often too bulky for GPU computation.