A 3.4- \mu W Object-Adaptive CMOS Image Sensor With Embedded Feature Extraction Algorithm for Motion-Triggered Object-of-Interest Imaging

• Published in: IEEE journal of solid-state circuits 2014-01, Vol.49 (1), p.289-300
• Main Authors: Choi, Jaehyuk, Park, Seokjun, Cho, Jihyun, Yoon, Euisik
• Format: Article
• Language: English
• Subjects: Bandwidth; Capacitors; CMOS image sensor; Feature extraction; Imaging; low power; motion detection; Power demand; Wireless sensor networks
• ISSN: 0018-9200; 1558-173X
• DOI: 10.1109/JSSC.2013.2284350

We report a low-power object-adaptive CMOS imager, which suppresses spatial temporal bandwidth. The object-adaptive imager has embedded a feature extraction algorithm for identifying objects of interest. The sensor wakes up triggered by motion sensing and extracts features from the captured image for the detection of object-of-interest (OOI). Full-image capturing operation and image signal transmission are performed only when the interested objects are found, which significantly reduces power consumption at the sensor node. This motion-triggered OOI imaging significantly saves a spatial bandwidth more than 96.5% from the feature output and saves a temporal bandwidth from the motion-triggered wakeup and object adaptive imaging. The sensor consumes low power by employing a reconfigurable differential-pixel architecture with reduced power supply voltage and by implementing the feature extraction algorithm with mixed-signal circuitry in a small area. The chip operates at 0.22 μW/frame in motion-sensing mode and at 3.4 μW/frame for feature extraction, respectively. The object detection from on-chip feature extraction circuits has demonstrated a 94.5% detection rate for human from a set of 200 sample images.