TY - GEN
T1 - UbiPoint: towards non-intrusive mid-air interaction for hardware constrained smart glasses
AU - Lee, Lik Hang
AU - Braud, Tristan
AU - Bijarbooneh, Farshid Hassani
AU - Hui, Pan
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/5/27
Y1 - 2020/5/27
N2 - Throughout the past decade, numerous interaction techniques have been designed for mobile and wearable devices. Among these devices, smartglasses mostly rely on hardware interfaces such as touchpad and buttons, which are often cumbersome and counterintuitive to use. Furthermore, smartglasses feature cheap and low-power hardware preventing the use of advanced pointing techniques. To overcome these issues, we introduce UbiPoint, a freehand mid-air interaction technique. UbiPoint uses the monocular camera embedded in smartglasses to detect the user's hand without relying on gloves, markers, or sensors, enabling intuitive and non-intrusive interaction. We introduce a computationally fast and light-weight algorithm for fingertip detection, which is especially suited for the limited hardware specifications and the short battery life of smartglasses. UbiPoint processes pictures at a rate of 20 frames per second with high detection accuracy - no more than 6 pixels deviation. Our evaluation shows that UbiPoint, as a mid-air non-intrusive interface, delivers a better experience for users and smart glasses interactions, with users completing typical tasks 1.82 times faster than when using the original hardware.
AB - Throughout the past decade, numerous interaction techniques have been designed for mobile and wearable devices. Among these devices, smartglasses mostly rely on hardware interfaces such as touchpad and buttons, which are often cumbersome and counterintuitive to use. Furthermore, smartglasses feature cheap and low-power hardware preventing the use of advanced pointing techniques. To overcome these issues, we introduce UbiPoint, a freehand mid-air interaction technique. UbiPoint uses the monocular camera embedded in smartglasses to detect the user's hand without relying on gloves, markers, or sensors, enabling intuitive and non-intrusive interaction. We introduce a computationally fast and light-weight algorithm for fingertip detection, which is especially suited for the limited hardware specifications and the short battery life of smartglasses. UbiPoint processes pictures at a rate of 20 frames per second with high detection accuracy - no more than 6 pixels deviation. Our evaluation shows that UbiPoint, as a mid-air non-intrusive interface, delivers a better experience for users and smart glasses interactions, with users completing typical tasks 1.82 times faster than when using the original hardware.
UR - http://www.scopus.com/inward/record.url?scp=85086760440&partnerID=8YFLogxK
U2 - 10.1145/3339825.3391870
DO - 10.1145/3339825.3391870
M3 - Conference article published in proceeding or book
AN - SCOPUS:85086760440
T3 - MMSys 2020 - Proceedings of the 2020 Multimedia Systems Conference
SP - 190
EP - 201
BT - MMSys 2020 - Proceedings of the 2020 Multimedia Systems Conference
PB - Association for Computing Machinery, Inc
T2 - 11th ACM Multimedia Systems Online Conference, MMSys 2020
Y2 - 8 June 2020 through 11 June 2020
ER -