A Data-Compressive 1.5/2.75-bit Log-Gradient QVGA Image Sensor With Multi-Scale Readout for Always-On Object Detection

Abstract

This article presents an application-optimized QVGA image sensor for low-power, always-on object detection using histograms of oriented gradients (HOG). In contrast to conventional CMOS imagers that feature linear and high-resolution ADCs, our readout scheme extracts logarithmic intensity gradients at 1.5 or 2.75 bits of resolution. This eliminates unnecessary illumination-related data and allows the HOG feature descriptors to be compressed by up to $25\times $ relative to a conventional 8-bit readout. As a result, the digital backend-detector, which typically limits system efficiency, incurs less data movement and computation, leading to an estimated $3.3\times $ energy reduction. The imager employs a column-parallel readout with analog cyclic-row buffers that also perform arbitrary-sized pixel-binning for multi-scale object detection. The log-digitization of pixel gradients is computed using a ratio-to-digital converter (RDC), which performs successive capacitive divisions to its input voltages. The prototype IC was fabricated in a 0.13- $\mu \text{m}$ CIS process with standard 4-T 5- $\mu \text{m}$ pixels and consumes 99 pJ/pixel. Experiments using a deformable parts model (DPM) detector for three object classes (persons, bicycles, and cars) indicate detection accuracies that are on par with conventional systems.