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Ninth IEEE International Symposium on Wearable Computers (ISWC'05)
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
Osaka, Japan
October 18-October 21
ISBN: 0-7695-2419-2
ASCII Text
x 
 
Donald J. Patterson, Dieter Fox, Henry Kautz, Matthai Philipose, "Fine-Grained Activity Recognition by Aggregating Abstract Object Usage," Wearable Computers, IEEE International Symposium, pp. 44-51, Ninth IEEE International Symposium on Wearable Computers (ISWC'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/ISWC.2005.22,
author = {Donald J. Patterson and Dieter Fox and Henry Kautz and Matthai Philipose},
title = {Fine-Grained Activity Recognition by Aggregating Abstract Object Usage},
journal ={Wearable Computers, IEEE International Symposium},
volume = {0},
year = {2005},
isbn = {0-7695-2419-2},
pages = {44-51},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISWC.2005.22},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Wearable Computers, IEEE International Symposium
TI - Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
SN - 0-7695-2419-2
SP44
EP51
A1 - Donald J. Patterson,
A1 - Dieter Fox,
A1 - Henry Kautz,
A1 - Matthai Philipose,
PY - 2005
KW - null
VL - 0
JA - Wearable Computers, IEEE International Symposium
ER -
 
Donald J. Patterson, University of Washington Department of Computer Science and Engineering Seattle, Washington, USA
Dieter Fox, University of Washington Department of Computer Science and Engineering Seattle, Washington, USA
Henry Kautz, University of Washington Department of Computer Science and Engineering Seattle, Washington, USA
Matthai Philipose, Intel Research Seattle, Seattle, Washington, USA

In this paper we present results related to achieving finegrained activity recognition for context-aware computing applications. We examine the advantages and challenges of reasoning with globally unique object instances detected by an RFID glove. We present a sequence of increasingly powerful probabilistic graphical models for activity recognition. We show the advantages of adding additional complexity and conclude with a model that can reason tractably about aggregated object instances and gracefully generalizes from object instances to their classes by using abstraction smoothing. We apply these models to data collected from a morning household routine.

Citation:
Donald J. Patterson, Dieter Fox, Henry Kautz, Matthai Philipose, "Fine-Grained Activity Recognition by Aggregating Abstract Object Usage," iswc, pp.44-51, Ninth IEEE International Symposium on Wearable Computers (ISWC'05), 2005
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