research-article

Tell me what i see: recognize RFID tagged objects in augmented reality systems

Authors:

Sanglu LuAuthors Info & Claims

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Pages 916 - 927

https://doi.org/10.1145/2971648.2971661

Published: 12 September 2016 Publication History

Abstract

Nowadays, people usually depend on augmented reality (AR) systems to obtain an augmented view in a real-world environment. With the help of advanced AR technology (e.g. object recognition), users can effectively distinguish multiple objects of different types. However, these techniques can only offer limited degrees of distinctions among different objects and cannot provide more inherent information about these objects. In this paper, we leverage RFID technology to further label different objects with RFID tags. We deploy additional RFID antennas to the COTS depth camera and propose a continuous scanning-based scheme to scan the objects, i.e., the system continuously rotates and samples the depth of field and RF-signals from these tagged objects. In this way, by pairing the tags with the objects according to the correlations between the depth of field and RF-signals, we can accurately identify and distinguish multiple tagged objects to realize the vision of "tell me what I see" from the augmented reality system. For example, in front of multiple unknown people wearing RFID tagged badges in public events, our system can identify these people and further show their inherent information from the RFID tags, such as their names, jobs, titles, etc. We have implemented a prototype system to evaluate the actual performance. The experiment results show that our solution achieves an average match ratio of 91% in distinguishing up to dozens of tagged objects with a high deployment density.

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Cited By

Shang FYang PXiong JFeng YLi X(2023)Tamera: Contactless Commodity Tracking, Material and Shopping Behavior Recognition Using COTS RFIDsACM Transactions on Sensor Networks10.1145/356377719:2(1-24)Online publication date: 3-Feb-2023
https://dl.acm.org/doi/10.1145/3563777
Boroushaki TLam MChen WDodds LEid AAdib F(2023)Exploiting Synergies between Augmented Reality and RFIDs for Item Localization and Retrieval2023 IEEE International Conference on RFID (RFID)10.1109/RFID58307.2023.10178452(30-35)Online publication date: 13-Jun-2023
https://doi.org/10.1109/RFID58307.2023.10178452
Dai FLi FZhao LMa F(2023)Intelligent Warehouse Material Detection Based on RFID and Deep Learning2023 International Conference on Networks, Communications and Intelligent Computing (NCIC)10.1109/NCIC61838.2023.00032(157-161)Online publication date: 17-Nov-2023
https://doi.org/10.1109/NCIC61838.2023.00032
Show More Cited By

Index Terms

Tell me what i see: recognize RFID tagged objects in augmented reality systems
1. Human-centered computing

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Information & Contributors

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Published In

cover image ACM Conferences

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 2016

1288 pages

ISBN:9781450344616

DOI:10.1145/2971648

General Chairs:
Paul Lukowicz
DFKI and University of Kaiserslautern
,
Antonio Krüger
DFKI and Saarland University
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics
,
Youn-Kyung Lim
KAIST
,
Shwetak N. Patel
University of Washington

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 September 2016

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Funding Sources

National Natural Science Foundation of China
EU FP7 IRSES MobileCloud Project
Natural Science Foundation of Jiangsu Province
NSF grants

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UbiComp '16

Sponsor:

UbiComp '16: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 12 - 16, 2016

Germany, Heidelberg

Acceptance Rates

UbiComp '16 Paper Acceptance Rate 101 of 389 submissions, 26%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Shang FYang PXiong JFeng YLi X(2023)Tamera: Contactless Commodity Tracking, Material and Shopping Behavior Recognition Using COTS RFIDsACM Transactions on Sensor Networks10.1145/356377719:2(1-24)Online publication date: 3-Feb-2023
https://dl.acm.org/doi/10.1145/3563777
Boroushaki TLam MChen WDodds LEid AAdib F(2023)Exploiting Synergies between Augmented Reality and RFIDs for Item Localization and Retrieval2023 IEEE International Conference on RFID (RFID)10.1109/RFID58307.2023.10178452(30-35)Online publication date: 13-Jun-2023
https://doi.org/10.1109/RFID58307.2023.10178452
Dai FLi FZhao LMa F(2023)Intelligent Warehouse Material Detection Based on RFID and Deep Learning2023 International Conference on Networks, Communications and Intelligent Computing (NCIC)10.1109/NCIC61838.2023.00032(157-161)Online publication date: 17-Nov-2023
https://doi.org/10.1109/NCIC61838.2023.00032
Lopez-De-Teruel PRuiz AGarcia-Clemente F(2023)Computer Vision Based Auto-ID for Optimizing Logistics Operations2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS)10.1109/COINS57856.2023.10189304(1-6)Online publication date: 23-Jul-2023
https://doi.org/10.1109/COINS57856.2023.10189304
Feng YHuang WWang SZhang YJiang SCao Z(2023)Anti-Clone: A Lightweight Approach for RFID Cloning Attacks DetectionCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-031-24386-8_5(75-90)Online publication date: 25-Jan-2023
https://doi.org/10.1007/978-3-031-24386-8_5
Ning JXie LWang CBu YXiao FYe BLu S(2022)Revolving Scanning on Tagged Objects: 3D Structure Detection of Logistics Packages via RFID SystemsACM Transactions on Sensor Networks10.1145/349017118:2(1-29)Online publication date: 16-Mar-2022
https://dl.acm.org/doi/10.1145/3490171
Zhang SMa ZYang CKui XLiu XWang WWang JGuo S(2022)Real-time and Accurate Gesture Recognition with Commercial RFID DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2022.3211324(1-16)Online publication date: 2022
https://doi.org/10.1109/TMC.2022.3211324
Zhang SMa ZLu KLiu XLiu JGuo SZomaya AZhang JWang J(2022)HearMe: Accurate and Real-time Lip Reading based on Commercial RFID DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2022.3208019(1-14)Online publication date: 2022
https://doi.org/10.1109/TMC.2022.3208019
Ding HZhao CWang GZhao KXi WZhao J(2022)Utilizing Tag Interference for Refined Localization of Passive RFIDIEEE Internet of Things Journal10.1109/JIOT.2021.31379689:14(12656-12672)Online publication date: 15-Jul-2022
https://doi.org/10.1109/JIOT.2021.3137968
Boroushaki TPerper INachin MRodriguez AAdib F(2021)RFusionProceedings of the 19th ACM Conference on Embedded Networked Sensor Systems10.1145/3485730.3485944(192-205)Online publication date: 15-Nov-2021
https://dl.acm.org/doi/10.1145/3485730.3485944
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