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Meshless Animation Framework

Authors: Johansen, Gustav Adolf;

Meshless Animation Framework

Abstract

This report details the implementation of a meshless animation framework for blending surfaces. The framework is meshless in the sense that only the control points are handled on the CPU, and the surface evaluation is delegated to the GPU using the tessellation shader steps. The framework handles regular grids and some forms of irregular grids. Different ways of handling the evaluation of the local surfaces are investigated. Directly evaluating them on the GPU or pre-evaluating them and only sampling the data on the GPU. Four different methods for pre-evaluation are presented, and the surface accuracy of each one is tested. The framework contains two methods for adaptively setting the level of detail on the GPU depending on position of the camera, using a view-based metric and a pixel-accurate rendering method. For both methods the pixel-accuracy and triangle size is tested and compared with static tessellation. Benchmarking results from the framework are presented. With and without animation, with different local surface types, and different resolution on the pre-evaluated data.

Keywords

VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Datateknologi: 551, VDP::Technology: 500::Information and communication technology: 550::Computer technology: 551

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green