Fine-grained activity recognition by aggregating abstract object usage
作者： D.J. Patterson , D. Fox , H. Kautz , M. Philipose
DOI: 10.1109/ISWC.2005.22
关键词: Smoothing 、 Graphical model 、 Computer science 、 Artificial intelligence 、 Sequence 、 Activity recognition 、 Mobile computing 、 Machine learning 、 Unique object 、 Abstraction (linguistics) 、 Object (computer science)
摘要: 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. a sequence increasingly powerful probabilistic graphical models recognition. show adding additional complexity conclude model that can reason tractably about aggregated gracefully generalizes from their classes using abstraction smoothing. apply these data collected morning household routine.
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