Paper Info
Title
Trajectory-Assisted Robust RFID-tagged Object Tracking and Recognition in Room Environment
Abstract
ABSTRACTThis paper takes a Computer-Vision (CV) and RFID fusion approach to tracking RFID-tagged objects in a room environment. Unlike similar CV-RFID fusion techniques that fuse two different estimates from CV and RFID systems to increase the certainty of locations, our system does not directly localize RFID tags. Instead, each tag-attached object's usage time by a human is detected by observation of the tag's phase variance. The time is then used to identify the pinpoint locations where the object is handed and released by the human, using the corresponding human trajectory observed by 3D depth cameras. RSSI variance caused by human movement is also leveraged to estimate rough locations of such objects that are not used by humans. Finally, the correspondence between the objects and RFID tags is automatically recognized by clustering the feature vectors of objects. Consequently, once the type of one object, such as pen, book, and cup, the other objects in the cluster can be annotated with the same object type to facilitate object management in the system. The experimental results have shown that object usage is detected with 0.984 accuracy, objects are localized with 58.3cm median error in severe NLoS environment, and ten types of objects are identified with 0.842 accuracy in a laboratory room.
Year
DOI
Venue
2020
10.1145/3416010.3423241
Modeling, Analysis and Simulation of Wireless and Mobile Systems
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Motoki Ougida100.34
Hirozumi Yamaguchi237160.93
Higashino, T.31915.19