Adaptively Sampled Distance Fields (ADFs)
ADFs are a new digital representation of shape with several advantages over existing approaches. They provide efficient and accurate representation of both smoothly curved surfaces and surfaces with fine detail. ADFs have the potential to impact many diverse industries including CAD/CAM (simulation, path planning, and verification for milling precision parts), Entertainment (building models for games and movies), Fonts (high-quality display of letterforms for PDAs), Visualization (volumetric visualization of molecular structure), 3D Scanning (3D models from image or range data), 3D Printing (rapid prototyping), and Color Management (projectors, PDAs, monitors, and printers).
Background & Objective: Our objectives include fundamental research, incorporation of this research into a product-worthy C library ready for commercialization, development of a comprehensive patent portfolio, and collaboration with key industrial players to refine and expand the vision for ADFs.
Technical Discussion: A distance field is a scalar field that specifies a distance to a shape, where the distance may be signed to distinguish between the inside and outside of the shape. ADFs consist of adaptively sampled distance values, organized in a spatial data structure, with a method for reconstructing the distance field from the sampled distance values. This approach permits the accurate and compact representation of fine detail and smooth surfaces, together with efficient processing. ADFs allow: the representation of more than the surface (interiors and exteriors); the compact representation of sharp features and organic shapes; smooth surface reconstruction; trivial inside/outside and proximity testing; fast and simple CSG operations; fast geometric queries such as closest point; and efficient computation of surface offsetting, blending and filleting, collision detection, morphing, and rough cutting.
Contact: Ron Perry
Publications:
Frisken, S.F.; Perry, R.N., "Computing 3D Geometry Directly from Range Images", ACM SIGGRAPH, August 2001 (Sketches and Applications, TR2001-010)
Pope, J.; Frisken, S.F.; Perry, R.N., "Dynamic Meshing Using Adaptively Sampled Distance Fields", ACM SIGGRAPH, August 2001 (Sketches & Applications, TR2001-013)
Frisken, S.F.; Perry, R.N., "A Computationally Efficient Framework for Modeling Soft Body Impact", ACM SIGGRAPH, August 2001 (Sketches & Applications, TR2001-011)
Perry, R.N.; Frisken, S.F., "Kizamu: A System for Sculpting Digital Characters", ACM SIGGRAPH, ISBN: 1-58113-374-X, pp. 47-56, August 2001 (ACM Press, TR2001-008)
Frisken, S.F.; Perry, R.N.; Rockwood, A.P.; Jones, T.R., "Adaptively Sampled Distance Fields: A General Representation of Shape for Computer Graphics", ACM SIGGRAPH, ISBN: 1-58113-208-5, pps 249-254, July 2000 (Proc ACM Press, TR2000-015)
| Technical Reports: | |
| A New Framework For Non-Photorealistic Rendering | |
| A New Representation for Device Color Gamuts | |
| Calculating the Distance Map for Binary Sampled Data | |
| Using Distance Maps for Accurate Surface Representation in Sampled Volumes | |
Technology Area: Graphics
Modification Date: September 12, 2007