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Near Real-Time Cutting. Paul F. Neumann. Dept. of Ophthalmology and Visual Sciences. College of Health and Human Development Sciences, University of Illinois at Chicago. Virtual Reality Surgical Simulators. Simulate the functionality of surgical instruments such as blades and
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Near Real-Time Cutting Paul F. Neumann Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Virtual Reality Surgical Simulators • Simulate the functionality • of surgical instruments • such as blades and • scissors • A general 3D cutting • algorithm is a one of • challenging problems. • Simulators must maintain • an interactive frame rate. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Previous Cutting Algorithms 1988 Tearing (Terzopoulos and Fleischer) 1992 Particle Systems (Szeliski and Tonnesen) 1992 Radial Projection on FEM (Pieper et al.) 1995 2D FEM Template (Song and Reddy) 1997 3D FEM with Bilinear Cutting Plane (Mazura and Seifert) 1997 Boolean Operations (Delp et al.) 1998 Hybrid Elastic Model (Colin et al.) My Goal: To develop an interactive cutting algorithm on a mass-spring system with a polygonal surface. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Mass-Spring System • Very popular PBM platform • Vertices as mass points • Edges as vector springs • Dynamic system which permits • insertions and deletions • Distributes mass appropriately • Conserves surface area Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Vector Springs • Invented by Alan Millman at EVL • Maintain their orientation and length • Easy to subdivide Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Algorithm Overview 1) Samples blade’s path. 2) Reconstructs the path with a series of parallelograms. 3) Intersects and subdivides springs and triangles. 4) Recomputes mass and spring stiffness coefficients. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Reconstructing Cutting Path • Discretely samples path. • Drop samples if roughly co-planar. • Fit parallelogram through two selected samples by • averaging orientation and adding offset. • Parallelograms lag behind current position. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Intersection Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Subdivision Intersection Spring Subdivision Triangle Subdivision Further Subdivision New interior springs must compute their rest direction through vector addition of their neighbors. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Mass Distribution: Localized Approximation • Mass proportional to surface area • at rest. • New vertices and their neighbors • have their mass values • recomputed after subdivision. • Spring rest direction vectors • outline the undeformed triangle • area. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Cutting Example Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Cutting Example Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Cutting Example Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Cutting Example Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Cutting Example Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Cutting Example Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Variations Suction Cutter Tearing Scissors Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Video Tape Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
Discussion • Geometry dependence. • Lag in response time. • Rounds to nearest vertex. • Collision Detection • Small parallelograms within a • triangle aren’t processed. Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago
More Information A more detailed paper is included on your Application cdrom. Web Site: www.bvis.uic.edu/paul/ CAL Demonstration right after session Dept. of Ophthalmology and Visual Sciences College of Health and Human Development Sciences, University of Illinois at Chicago