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2004
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Mining models of human activities from the web

11 years 3 months ago
Mining models of human activities from the web
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A system that can do this requires models of the activities of interest, but model construction does not scale well: humans must specify lowlevel details, such as segmentation and feature selection of sensor data, and high-level structure, such as spatio-temporal relations between states of the model, for each and every activity. As a result, previous practical activity recognition systems have been content to model a tiny fraction of the thousands of human activities that are potentially useful to detect. In this paper, we present an approach to sensing and modeling activities that scales to a much larger class of activities than before. We show how a new class of sensors, based on Radio Frequency Identification (RFID) tags, can directly yield semantic terms that describe the state of the physical world. These...
Mike Perkowitz, Matthai Philipose, Kenneth P. Fish
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2004
Where WWW
Authors Mike Perkowitz, Matthai Philipose, Kenneth P. Fishkin, Donald J. Patterson
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