Aditya Bagaria

dblp:383/8480 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0009-8068-6623ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 44% Ubiquitous computing and smart environments · 44% Interaction techniques and input · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments › smart home
smart home interaction
0.812024
IRIS: Wireless ring for vision-based smart home interaction · UIST 2024
Wearable and physiological sensing › smart wearable
smart ring
0.812024
IRIS: Wireless ring for vision-based smart home interaction · UIST 2024
Interaction techniques and input
gesture input
0.212024
IRIS: Wireless ring for vision-based smart home interaction · UIST 2024

Methods — techniques the papers use, named apart from their topics

scene semantics · 0.8instance-level device recognition · 0.8
YearPublicationVenuePosition
2024 IRIS: Wireless ring for vision-based smart home interaction
abstract
Integrating cameras into wireless smart rings has been challenging due to size and power constraints. We introduce IRIS, the first wireless vision-enabled smart ring system for smart home interactions. Equipped with a camera, Bluetooth radio, inertial measurement unit (IMU), and an onboard battery, IRIS meets the small size, weight, and power (SWaP) requirements for ring devices. IRIS is context-aware, adapting its gesture set to the detected device, and can last for 16-24 hours on a single charge. IRIS leverages the scene semantics to achieve instance-level device recognition. In a study involving 23 participants, IRIS consistently outpaced voice commands, with a higher proportion of participants expressing a preference for IRIS over voice commands regarding toggling a device’s state, granular control, and social acceptability. Our work pushes the boundary of what is possible with ring form-factor devices, addressing system challenges and opening up novel interaction capabilities.
Maruchi Kim, Antonio Glenn, Bandhav Veluri, Yunseo Lee, Eyoel Gebre, Aditya Bagaria, Shwetak N. Patel, Shyamnath Gollakota
UIST6