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

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.