A 3.0μw@5fps QQVGA Self-Controlled Wake-Up Imager with On-Chip Motion Detection, Auto-Exposure and Object Recognition
2020 IEEE SYMPOSIUM ON VLSI CIRCUITS(2020)
摘要
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.
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关键词
QQVGA self-controlled wake-up,self-controlled capabilities,multimodality event-of-interest detection,high-quality imaging,CMOS technology,standard 4T pixels,on-chip object recognition,battery-powered systems,image content analysis,On-Chip Motion Detection,face detection use case,single-scale object recognition,background subtraction,QQVGA resolution,power consumption figures,on-chip automation,log-domain auto-exposure algorithm,low-power applications,power 3.0 muW to 5.7 muW,power 3.0 muW,power 10.0 muW,size 90.0 nm
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