A hybrid motion prediction method for caching and prefetching in distributed virtual environments

Addison Chan, Rynson W. H. Lau, Beatrice Ng

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

19 Citations (Scopus)

Abstract

Although there are a few methods proposed for predicting 3D motion, most of these methods are primarily designed for predicting the motion of specific objects, by assuming certain object motion behaviors. We notice that in desktop distributed 3D applications, such as virtual walkthrough and computer games, the 2D mouse is still the most popular device being used as navigation input. Through studying the motion behavior of a mouse during 3D navigation, we propose a hybrid motion model for predicting the mouse motion during a 3D walkthrough. At low motion velocity, we use a linear model for prediction and at high motion velocity, we use an elliptic model for prediction. We describe how this prediction method can be integrated into our distributed virtual environment for object model caching and prefetching. We also demonstrate the effectiveness of the prediction method and the resulting caching and prefetching mechanisms through extensive experiments.
Original languageEnglish
Title of host publicationACM Symposium on Virtual Reality Software and Technology, Proceedings, VRST
Pages135-142
Publication statusPublished - 2001
EventProceedings of the ACM Symposium on Virtual Reality Software and Technology (VRST 2001) - Banff, Alta., Canada
Duration: 15 Nov 200117 Nov 2001

Conference

ConferenceProceedings of the ACM Symposium on Virtual Reality Software and Technology (VRST 2001)
Country/TerritoryCanada
CityBanff, Alta.
Period15/11/0117/11/01

Research Keywords

  • 3D navigation
  • Caching
  • Distributed virtual environments
  • Motion prediction
  • Prefetching
  • Virtual walkthrough

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