An experiment in hierarchical recognition of group activities using wearable sensors

Authors:
Dawud Gordon;Jan-Hendrik Hanne;Martin Berchtold;Takashi Miyaki;Michael Beigl
Affiliations:
Karlsruhe Institute of Technology, Karlsruhe, Germany;Technische Universität Braunschweig, Brunswick, Germany;Technische Universität Braunschweig, Brunswick, Germany;Karlsruhe Institute of Technology, Karlsruhe, Germany;Karlsruhe Institute of Technology, Karlsruhe, Germany
Venue:
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
Year:
2011

Citing 3
Cited 1

Mediacups: experience with design and use of computer-augmented everyday artefacts

Computer Networks: The International Journal of Computer and Telecommunications Networking - pervasive computing
Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors

LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Investigation of Context Prediction Accuracy for Different Context Abstraction Levels

IEEE Transactions on Mobile Computing

Towards Collaborative Group Activity Recognition Using Mobile Devices

Mobile Networks and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pervasive computing envisions implicit interaction between people and their intelligent environments instead of individual devices, inevitably leading to groups of individuals interacting with the same intelligent environment. These environments must therefore be aware not only of user contexts and activities, but the contexts and activities of groups of users as well. This poster will demonstrate an experiment conducted towards understanding hierarchical multi-user group activity recognition using wearable sensors. The experiment will explore different data abstraction levels in terms of recognition rates, power consumption and wireless communication volumes for the devices involved.