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:
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage (author’s PDF), by Donald Patterson, Dieter Fox, Henry Kautz, Matthai Philipose (U. Washington and Intel Research, Seattle)
ReachMedia: On-the-move interaction with everyday objects (author’s PDF), by Assaf Feldman, Emmanuel Munguia Tapia, Sajid Sadi, Pattie Maes and Chris Schmandt (MIT Media Lab)
A Design Process for the Development of Innovative Smart Clothing that Addresses End-User Needs from Technical, Functional, Aesthetic and Cultural View Points by Jane McCann, Richard Hurford and Adam Martin (University of Wales)
Pictorial Depth Cues for Outdoor Augmented Reality by Jason Wither and Tobias Höllerer (University of California, Santa Barbara)
A Body-mounted Camera System for Capturing User-view Images without Head- mounted Camera by Hirotake Yamazoe, Akira Utsumi and Kenichi Hosaka (ATR)
The Impacts of Limited Visual Feedback on Mobile Text Entry for the Twiddler and Mini-QWERTY Keyboard (author’s PDF) by James Clawson, Kent Lyons, Thad Starner and Edward Clarkson (Georgia Tech)