IDSense: A Human Object Interaction Detection System Based on Passive UHF RFID

Authors

Hanchuan Li (University of Washington, Disney Research Pittsburgh)
Can Ye (Disney Research Pittsburgh)
Alanson Sample (Disney Research Pittsburgh)

ACM Conference on Human Factors in Computing Systems (CHI) 2015

April 18, 2015

IDSense A Human Object Interaction Detection System Based on Passive UHF RFID-Image

Types of human-object interactions a) translation b) rotation c) swipe touch d) cover touch

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.

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