college of health and human development sciences, university of illinois at chicago
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Near Near
Real-TimeReal-Time
CuttingCutting
Paul F. Neumann
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
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.
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
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.
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
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
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Vector Springs
• Invented by Alan Millman at EVL
• Maintain their orientation and length
• Easy to subdivide
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
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.
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
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.
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Intersection
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Subdivision
New interior springs must compute their rest directionthrough vector addition of their neighbors.
Intersection SpringSubdivision
TriangleSubdivision
FurtherSubdivision
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
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.
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Cutting Example
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Cutting Example
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Cutting Example
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Cutting Example
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Cutting Example
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Cutting Example
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Variations
Suction Cutter Tearing
Scissors
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Video Tape
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
Discussion
• Geometry dependence.
• Lag in response time.
• Rounds to nearest vertex.
• Collision Detection
• Small parallelograms within a
triangle aren’t processed.
College of Health and Human Development Sciences, University of Illinois at Chicago
Dept. of Ophthalmology and Visual Sciences
More Information
A more detailed paper is included on
your Application cdrom.
Web Site:
www.bvis.uic.edu/paul/
CAL Demonstration right after session