Donald J. Patterson

Fine-Grained Activity Recognition by Aggregating Abstract Object Usage

Fine-Grained Activity Recognition by Aggregating Abstract Object Usage

In this paper we present results related to achieving fine grained 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.( permanent, local copy )

Published in International Symposium on Wearable Computing – ISWC 2005

C.V.: CR-06

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