ISWC Best Paper winner


The winner of this year’s best paper award at ISWC (the first ISWC to have such an award) was a paper by Don Patterson from the University of Washington called Fine-Grained Activity Recognition by Aggregating Abstract Object Usage. All the authors got certificates and Don took home a new video iPod as the prize.

This was one of several papers presented that used an RFID reader in a glove, in this case to classify what kind of activity a person is conducting based on the sequence of objects she has touched. This would be useful, for example, for alerting a care worker if a resident of an assistive-living home had stopped eating.

From the abstract:

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.

Here are all six nominees for best paper from ISWC’05, which were the top 10% of full papers based on reviewer-rating: