Name
Abstract | ||
|---|---|---|
In order to enable unobtrusive human object interaction detection, we propose a minimalistic approach to instrumenting everyday objects with passive (i.e. battery-free) UHF RFID tags. By measuring the changes in the physical layer of the communication channel between the RFID tag and reader (such as RSSI, RF phase, and read rate) we are able to classify, in real time, tag/object motion events along with two types of touch events. Through a user study, we demonstrate that our real-time classification engine is able to simultaneously track 20 objects and identify four movement classes with 93% accuracy. To demonstrate how robust this general-purpose interaction mechanism is, we investigate three usage scenarios 1) interactive storytelling with toys 2) inference of daily activities in the home 3) identification of customer browsing habits in a retail setting. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2702123.2702178 | CHI |
Keywords | Field | DocType |
rfid,touch interface,miscellaneous,activity detection,object interaction | Computer science,Inference,Communication channel,Human–computer interaction,Activity detection,Physical layer,Interactive storytelling,Ultra high frequency | Conference |
Citations | PageRank | References |
46 | 1.56 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanchuan Li | 1 | 89 | 5.08 |
| Can Ye | 2 | 46 | 1.56 |
| Alanson P Sample | 3 | 186 | 16.26 |