• DocumentCode
    2064444
  • 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
  • fYear
    2015
  • fDate
    22-26 Feb. 2015
  • Firstpage
    1
  • Lastpage
    3
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid- State Circuits Conference - (ISSCC), 2015 IEEE International
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    978-1-4799-6223-5
  • Type

    conf

  • DOI
    10.1109/ISSCC.2015.7063058
  • Filename
    7063058