| Authors |
Hyeon-Gu Do; Seongrim Choi; Junsik Woo; Ara Kim; Byeong-Gyu Nam |
| DOI |
https://doi.org/10.5573/JSTS.2019.19.4.404 |
| Keywords |
Wake-up detector ; gesture recognition ; energy-harvesting ; dual-mode CMOS image sensor ; subthreshold SRAM ; |
| Abstract |
Hand gesture recognition is one of the secure natural user interface (NUI) mechanisms on wearable devices since it does not reveal user’s intention in public domain. However, its energy dissipation is very demanding since it requires compute-intensive machine vision processing. Recently, wake-up detectors have been proposed to improve the energy-efficiency of always-on sensing nature of the NUI systems by switching off the main functional blocks while just keeping the wake-up detector alive during idle time. However, vision-based wake-up detectors still require power-consuming vision processing so we propose a self-powered vision wake-up detector to alleviate burdens on limited battery lifetime and thus facilitate always-on wake-up detection for the wearable gesture UIs. Our work has four key features to realize the self-powered wake-up detection; 1) near-threshold imaging-harvesting dual-mode CMOS image sensor (CIS) with 0.6 V 3T pixels, 2) subthreshold SRAM with disturb-free 0.3 V 10T bitcells, 3) hand detection engine with skin-color invariant Haar-like filters, and 4) on-die switched capacitor DC-DC converter for lightweight system design. Thanks to these features integrated together, this work achieves self-powered operation of always-on vision wake-up detection. |