Energy-Oriented Designs of an Augmented-Reality Application on a VUZIX Blade Smart Glass

The advent of wearable devices introduces many opportunities with unconventional computing paradigms. In this work, we investigate energy-efficient designs of an augmented-reality application, FaceReminder, on a VUZIX Blade (R) smart glass by exploiting its unique see-through display and on-board camera. Powered with well-known facial recognition techniques, FaceReminder aims at helping people with prosopagnosia (i.e., face blindness) or short-memory of face-name connection by showing the names of the person on the see-through display. To cope with the limited resources (especially battery) of the smart glass, we explore designs that offload portion of the computation in facial detection and recognition to another mobile device (e.g., smart phone), which pairs with the glass via Bluetooth. Several optimization techniques, such as resolution adjustment and cropping, have been investigated to improve the latency and energy efficiency with reduced image sizes. We implemented FaceReminder and empirically evaluated its accuracy, latency and energy consumption of the major steps (including photo taking, resizing/cropping, Bluetooth transmission, facial detection and recognition). Compared to the baseline Glass-Only design, the most efficient Paired Glass-Device design with photos of reduced resolution and MTCNN facial detection technique can reduce the average latency by 73% and energy consumption by 78:9% (i.e., about 5X battery life improvement) while maintaining more than satisfactory 80% recognition accuracy.