Title :
18.1 A 2.71nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile HMD applications
Author :
Injoon Hong ; Kyeongryeol Bong ; Dongjoo Shin ; Seongwook Park ; Kyuho Lee ; Youchang Kim ; Hoi-Jun Yoo
Author_Institution :
KAIST, Daejeon, South Korea
Abstract :
Smart eyeglasses or head-mounted displays (HMDs) have been gaining traction as next-generation mainstream wearable devices. However, previous HMD systems [1] have had limited application, primarily due to their lacking a smart user interface (Ul) and user experience (UX). Since HMD systems have a small compact wearable platform, their Ul requires new modalities, rather than a computer mouse or a 2D touch panel. Recent speech-recognition-based Uls require voice input to reveal the user´s intention to not only HMD users but also others, which raises privacy concerns in a public space. In addition, prior works [2-3] attempted to support object recognition (OR) or augmented reality (AR) in smart eyeglasses, but consumed considerable power, >381mW, resulting in <;6 hours operation time with a 2100mWh battery.
Keywords :
helmet mounted displays; object recognition; speech recognition; 2D touch panel; 3D-stacked gaze-activated object-recognition system; AR; OR; UX; Ul; augmented reality; computer mouse; head-mounted display; low-power mobile HMD application; next-generation mainstream wearable device; smart eyeglass; smart user interface; speech-recognition; user experience; Electrooculography; Estimation; Feature extraction; Table lookup; Three-dimensional displays; Vectors;
Conference_Titel :
Solid- State Circuits Conference - (ISSCC), 2015 IEEE International
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4799-6223-5
DOI :
10.1109/ISSCC.2015.7063058