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

  • Authors:
  • Addison Chan;Rynson W. H. Lau;Beatrice Ng

  • Affiliations:
  • City University of Hong Kong, Hong Kong;City University of Hong Kong, Hong Kong;City University of Hong Kong, Hong Kong

  • Venue:
  • VRST '01 Proceedings of the ACM symposium on Virtual reality software and technology
  • Year:
  • 2001

Quantified Score

Hi-index 0.00

Visualization

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.