A Context-Aware AR Navigation System Using Wearable Sensors

Authors:
Daisuke Takada;Takefumi Ogawa;Kiyoshi Kiyokawa;Haruo Takemura
Affiliations:
Graduate School of Information Science and Technology, Osaka University, Osaka, Japan 565-0871;Information Technology Center, The University of Tokyo, Tokyo, Japan 113-0032;Cybermedia Center, Osaka University, Osaka, Japan 560-0043;Cybermedia Center, Osaka University, Osaka, Japan 560-0043
Venue:
Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction
Year:
2009

Citing 6
Cited 0

Scalable data management using user-based caching and prefetching in distributed virtual environments

VRST '01 Proceedings of the ACM symposium on Virtual reality software and technology
A hybrid motion prediction method for caching and prefetching in distributed virtual environments

VRST '01 Proceedings of the ACM symposium on Virtual reality software and technology
A Touring Machine: Prototyping 3D Mobile Augmented Reality Systems for Exploring the Urban Environment

ISWC '97 Proceedings of the 1st IEEE International Symposium on Wearable Computers
Visual attention based information culling for Distributed Virtual Environments

Proceedings of the ACM symposium on Virtual reality software and technology
Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing context for annotating a live life recording

Personal and Ubiquitous Computing - Memory and Sharing of Experiences

Quantified Score

Hi-index	0.00

Visualization

Abstract

We have been developing a networked wearable AR system that determines the user's current context to provide appropriate annotations. This system allows for annotation management based on the relationship between annotations and the real environment along with data transfer routines that dynamically calculate annotations' priority to transfer just enough data from the annotation server to the wearable PC worn by the user. Furthermore, this system recognizes the user's activity to predict the kind and level of detail of annotations the user needs at a given time. This information can be used for dynamic annotation filtering and switching of rendering modes.