Communication Dans Un Congrès Année : 2024

A Workload Prediction Model for 3D Textured Meshes in Webgl Context

Gabriel Meynet
Jean Claude Iehl
Johanna Delanoy
Guillaume Lavoué
Florent Dupont

Résumé

The vast majority of simplification algorithms are based roughly on the assumption that rendering time is related to the number of primitives, with the aim of reducing memory impact and rendering complexity. In this paper, we define more precisely the links between 3D object intrinsic characteristics and rendering time in order to provide a new tool for prediction and to guide these simplification methods. We conduct a large-scale experiment in a WebGL environment on multiple devices to measure the rendering time of a set of photo-reconstructed and textured 3D meshes. The results showed us the influence of features on rendering time and that the number of vertices is not the most relevant characteristic. We then trained a predictor capable of predicting the rendering performance of a 3D mesh. This predictor takes as input various characteristics of 3D objects as well as a set of device rendering performance features that we have introduced and achieves a prediction accuracy of 1.16 ± 0.09 ms on average (19.70 ± 2.44 % relative error). We also provide an analysis of the most important characteristics for the task of prediction.

CCS CONCEPTS

• Computing methodologies → Classification and regression trees; Rendering; Graphics processors; Mesh models.

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Dates et versions

hal-04906916 , version 1 (22-01-2025)

Identifiants

Citer

Gabriel Meynet, Jean Claude Iehl, Johanna Delanoy, Guillaume Lavoué, Florent Dupont. A Workload Prediction Model for 3D Textured Meshes in Webgl Context. WEB3D '24: The 29th International ACM Conference on 3D Web Technology, Sep 2024, Guimarães, Portugal. pp.1-11, ⟨10.1145/3665318.3677156⟩. ⟨hal-04906916⟩
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