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Motion-aware adaptive dead reckoning algorithm for collaborative virtual environments

Authors :
Vasily Y. Kharitonov
Source :
VRCAI
Publication Year :
2012
Publisher :
ACM, 2012.

Abstract

Dead reckoning algorithms are employed in collaborative virtual environments (CVEs) for predicting virtual objects states at any given moment of time that makes it possible to minimize bandwidth requirements while maintaining required data consistency. However, existing implementations often do not take into account information on the object motion dynamics and, in general, apply static prediction models. In this paper a novel motion-aware adaptive dead reckoning algorithm (MAADR) is introduced based on dynamical prediction model selection depending on the object motion pattern. The results show that considerable reduction in a number of update messages can be achieved without sacrificing prediction accuracy. In addition, it becomes possible to dynamically adjust the size of update messages according to the motion pattern and, thus, provide more flexible use of network bandwidth.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
Accession number :
edsair.doi...........4133c5c1b7d4310c785c45ea16027f3a
Full Text :
https://doi.org/10.1145/2407516.2407577