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Andy Nealen

Researcher at University of Southern California

Publications -  74
Citations -  4438

Andy Nealen is an academic researcher from University of Southern California. The author has contributed to research in topics: Game mechanics & Game design. The author has an hindex of 23, co-authored 74 publications receiving 3957 citations. Previous affiliations of Andy Nealen include Technische Universität Darmstadt & Technical University of Berlin.

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Physically Based Deformable Models in Computer Graphics

TL;DR: This paper presents the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass‐spring systems, mesh‐free methods, coupled particle systems and reduced deformable models‐based on modal analysis.
Proceedings Article

Physically Based Deformable Models in Computer Graphics.

TL;DR: In this article, the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass-spring systems, mesh free methods, coupled particle systems and reduced deformable models based on modal analysis.
Proceedings ArticleDOI

Point based animation of elastic, plastic and melting objects

TL;DR: The physical model is derived from continuum mechanics, which allows the specification of common material properties such as Young's Modulus and Poisson's Ratio and it is demonstrated how to solve the equations of motion based on these forces, with both explicit and implicit integration schemes.
Proceedings ArticleDOI

FiberMesh: designing freeform surfaces with 3D curves

TL;DR: This system provides real-time algorithms for both control curve deformation and the subsequent surface optimization and it is shown that one can create sophisticated models using this system, which have not yet been seen in previous sketching or functional optimization systems.
Proceedings ArticleDOI

Laplacian mesh optimization

TL;DR: This work introduces a framework for triangle shape optimization and feature preserving smoothing of triangular meshes that is guided by the vertex Laplacian and the discrete mean curvature normal, and it is capable of smoothing the surface while preserving geometric features.