VueBuds: Visual Intelligence with Wireless Earbuds
arXiv:2603.29095v1 Announce Type: new Abstract: Despite their ubiquity, wireless earbuds remain audio-centric due to size and power constraints. We present VueBuds, the first camera-integrated wireless earbuds for egocentric vision, capable of operating within stringent power and form-factor limits. Each VueBud embeds a camera into a Sony WF-1000XM3 to stream visual data over Bluetooth to a host device for on-device vision language model (VLM) processing. We show analytically and empirically that while each camera's field of view is partially occluded by the face, the combined binocular perspective provides comprehensive forward coverage. By integrating VueBuds with VLMs, we build an end-to-end system for real-time scene understanding, translation, visual reasoning, and text reading; all f
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Abstract:Despite their ubiquity, wireless earbuds remain audio-centric due to size and power constraints. We present VueBuds, the first camera-integrated wireless earbuds for egocentric vision, capable of operating within stringent power and form-factor limits. Each VueBud embeds a camera into a Sony WF-1000XM3 to stream visual data over Bluetooth to a host device for on-device vision language model (VLM) processing. We show analytically and empirically that while each camera's field of view is partially occluded by the face, the combined binocular perspective provides comprehensive forward coverage. By integrating VueBuds with VLMs, we build an end-to-end system for real-time scene understanding, translation, visual reasoning, and text reading; all from low-resolution monochrome cameras drawing under 5mW through on-demand activation. Through online and in-person user studies with 90 participants, we compare VueBuds against smart glasses across 17 visual question-answering tasks, and show that our system achieves response quality on par with Ray-Ban Meta. Our work establishes low-power camera-equipped earbuds as a compelling platform for visual intelligence, bringing rapidly advancing VLM capabilities to one of the most ubiquitous wearable form factors.
Comments: CHI 2026
Subjects:
Human-Computer Interaction (cs.HC)
Cite as: arXiv:2603.29095 [cs.HC]
(or arXiv:2603.29095v1 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2603.29095
arXiv-issued DOI via DataCite (pending registration)
Related DOI:
https://doi.org/10.1145/3772318.3791322
DOI(s) linking to related resources
Submission history
From: Maruchi Kim [view email] [v1] Tue, 31 Mar 2026 00:29:33 UTC (19,793 KB)
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