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dc.contributor.authorChen, Wenqiang
dc.contributor.authorLin, Shupei
dc.contributor.authorPeng, Zhencan
dc.contributor.authorParizi, Farshid Salemi
dc.contributor.authorHeo, Seongkook
dc.contributor.authorPatel, Shwetak
dc.contributor.authorMatusik, Wojciech
dc.contributor.authorZhao, Wei
dc.contributor.authorStankovic, John
dc.date.accessioned2024-04-04T17:41:41Z
dc.date.available2024-04-04T17:41:41Z
dc.date.issued2024-03-06
dc.identifier.issn2474-9567
dc.identifier.urihttps://hdl.handle.net/1721.1/154071
dc.description.abstractKnowing the object grabbed by a hand can offer essential contextual information for interaction between the human and the physical world. This paper presents a novel system, ViObject, for passive object recognition that uses accelerometer and gyroscope sensor data from commodity smartwatches to identify untagged everyday objects. The system relies on the vibrations caused by grabbing objects and does not require additional hardware or human effort. ViObject's ability to recognize objects passively can have important implications for a wide range of applications, from smart home automation to healthcare and assistive technologies. In this paper, we present the design and implementation of ViObject, to address challenges such as motion interference, different object-touching positions, different grasp speeds/pressure, and model customization to new users and new objects. We evaluate the system's performance using a dataset of 20 objects from 20 participants and show that ViObject achieves an average accuracy of 86.4%. We also customize models for new users and new objects, achieving an average accuracy of 90.1%. Overall, ViObject demonstrates a novel technology concept of passive object recognition using commodity smartwatches and opens up new avenues for research and innovation in this area.en_US
dc.publisherACMen_US
dc.relation.isversionof10.1145/3643547en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceACMen_US
dc.subjectComputer Networks and Communicationsen_US
dc.subjectHardware and Architectureen_US
dc.subjectHuman-Computer Interactionen_US
dc.titleViObject: Harness Passive Vibrations for Daily Object Recognition with Commodity Smartwatchesen_US
dc.typeArticleen_US
dc.identifier.citationWenqiang Chen , Shupei Lin , Zhencan Peng , Farshid Salemi Parizi , Seongkook Heo , Shwetak Patel , Wojciech Matusik , Wei Zhao , and John Stankovic . 2024. ViObject: Harness Passive Vibrations for Daily Object Recognition with Commodity Smartwatches. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Article ( 2024), 26 pages.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journalProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologiesen_US
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2024-04-01T07:49:58Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2024-04-01T07:49:59Z
mit.journal.volume8en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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