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The smart floor: a mechanism for natural user identification and tracking

Authors:

Robert J. Orr,

Gregory D. AbowdAuthors Info & Claims

CHI EA '00: CHI '00 Extended Abstracts on Human Factors in Computing Systems

Pages 275 - 276

https://doi.org/10.1145/633292.633453

Published: 01 April 2000 Publication History

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Abstract

We have created a system for identifying people based on their footstep force profiles and have tested its accuracy against a large pool of footstep data. This floor system may be used to identify users transparently in their everyday living and working environments. We have created user footstep models based on footstep profile features and have been able to achieve a recognition rate of 93%. We have also shown that the effect of footwear is negligible on recognition accuracy.

References

[1]

Addlesee, M., Jones, A., Livesey, F., and Samaria, F. The ORL Active Floor. IEEE Personal Communications, October 1997, 35-41.

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[2]

Moore, A. and Lee, M. S. Efficient Algorithms for Minimizing Cross Validation Error. Proceedings of the 11th International Conference on Machine Learning, Morgan Kaufmann, 1994.

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CHI EA '00: CHI '00 Extended Abstracts on Human Factors in Computing Systems

April 2000

406 pages

ISBN:1581132484

DOI:10.1145/633292

Conference Chair:
Marilyn Tremaine
Drexel University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 April 2000

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Data-centric support of a smart walker in a ubiquitous-computing environment

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