Presentation
Towards Always-on Interaction: A Sub-mW Visual Wakeup Acceleration Subsystem for Smart Glasses
DescriptionAlways-on vision is essential for smart glasses, yet continuous visual-processing under stringent power budgets remains a major challenge. This work presents an always-on visual wakeup acceleration-engine for sub-milliwatt hand gesture recognition. A compact convolutional neural network (<13k parameters), trained on the HaGRID dataset, performs binary classification on 64×64 inputs achieving over 92% accuracy at 3b precision, requiring less than 9kB of memory. When executed on a flexible accelerator engine implemented in 7nm technology, at 100MHz, it consumes only 64nJ per frame, translating to always-on power of 11μW at 30FPS, enabling energy-efficient, always-on interaction for next-generation
smart-glasses.
smart-glasses.
Event Type
Research Manuscript
TimeTuesday, July 2810:30am - 10:43am PDT
LocationMtg Room 101B