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• W2150338977 abstract "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." @default.
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• W2150338977 date "2005-12-13" @default.
• W2150338977 modified "2023-09-27" @default.
• W2150338977 title "Fine-Grained Activity Recognition by Aggregating Abstract Object Usage" @default.
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• W2150338977 doi "https://doi.org/10.1109/iswc.2005.22" @default.
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