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Mark C. Surles

dblp:60/3643 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 1992
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorHuman-computer interaction and ubiquitous computing · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Computer animation and physical simulation · 50% Geometric modeling and processing · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
molecular modeling
0.011992
An algorithm with linear complexity for interactive, physically-based modeling of large proteins · SIGGRAPH 1992
Computer animation and physical simulation
physically-based modeling
0.011992
An algorithm with linear complexity for interactive, physically-based modeling of large proteins · SIGGRAPH 1992
Bioinformatics and computational biology › structural bioinformatics
protein structure
0.011992
An algorithm with linear complexity for interactive, physically-based modeling of large proteins · SIGGRAPH 1992

Methods — techniques the papers use, named apart from their topics

lagrange multiplier method · 0.0constraint solving · 0.0
YearPublicationVenuePosition
1992 Interactive Modeling Enhanced with Constraints and Physics with Applications in Molecular Modeling
abstract
Article Interactive modeling enhanced with constraints and physics with applications in molecular modeling Share on Author: Mark C. Surles View Profile Authors Info & Claims I3D '92: Proceedings of the 1992 symposium on Interactive 3D graphicsJune 1992 Pages 175–182https://doi.org/10.1145/147156.147196Online:01 June 1992Publication History 7citation314DownloadsMetricsTotal Citations7Total Downloads314Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Mark C. Surles
SI3D1
1992 An algorithm with linear complexity for interactive, physically-based modeling of large proteins
abstract
Physically-based modeling applications usually require batch processing for each frame of an animation or simulation.This paper describes a graphics modeling system, called Sculpr, that maintains physically-valid protein properties while a user interactively moves atoms.Sculpt models stiff properties such as bond lengths and angles as rigid constraints and models weak properties such as non-bonded interactions as potential energies.Sculpr continually satisfies the constraints and maintains a local energy minimum throughout user interaction.On a Silicon Graphics 240-GTX, Sculpt maintains 1,9 updates per second on a molecular model with 355 atoms ( 1065 variables, 1027 constraints, and 3465 potential energies).Performance decreases /r'nearly with increased problem size.This paper presents a Lagrange multiplier method with linear computational complexity that finds a constrained minimum for articulated figures with many more joints in their spines than in any limb (e.g.reptiles, mammals, and proteins).The method computes the Jacobian matrix of the constraints and solves a system of linear equations that results from muhiplying the Jacobian by its transpose.The paper proves that a sort of the Jacobian yields a band-diagonal pattern of nonzeros.The pattern does not change during a modeling session, so the sort can run during a pre-processing step.Multiplication and solution of band-diagonal matrices require computation that increases linearly with problem size.Previous applications of Lagrange multipliers to constrained, physically-based modeling did not take advantage of the constraint connectivity in the spine.They either required many iterations of a linear algorithm or few iterations of a quadratic algorithm for each frame of a simulation.This application finds a constrained minimum with a linear algorithm in a few iterations.Additionally, most of the algorithm's steps execute in parallel for increased performance, CR
Mark C. Surles
SIGGRAPH1