A 3.0μW@5fps QQVGA Self-Controlled Wake-Up Imager with On-Chip Motion Detection, Auto-Exposure and Object Recognition
Arnaud Verdant, William Guicquéro, Nicolas Royer, Guillaume Moritz, Sébastien Martin, Florent Lepin, Sylvain Choisnet, Fabrice Guellec, Benoît Deschamps, Sylvain Clerc, Jerome Chossat
Abstract
Analyzing image content usually comes at the expense of a power consumption incompatible with battery-powered systems. Aiming at proposing a solution to this problem, this paper presents an imager with full on-chip object recognition, consuming sub-10μW using standard 4T pixels in 90nm imaging CMOS technology, opening the path for both wake-up and high-quality imaging. It combines multi-modality event-of-interest detection with self-controlled capabilities, a key for low-power applications. It embeds a log-domain auto-exposure algorithm to increase on-chip automation. The power consumption figures range from 3.0 to 5.7μW at 5fps for a QQVGA resolution while enabling background subtraction and single-scale object recognition. This typically shows a measured 94% accuracy for a face detection use case.