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A Data-Compressive 1.5/2.75-bit Log-Gradient QVGA Image Sensor With Multi-Scale Readout for Always-On Object Detection Christopher Young , Student Member , IEEE
一种面向低功耗物体检测的QVGA图像传感器,采用对数梯度压缩技术,显著降低数据量和能耗。
0.13µm CIS工艺, 4-T 5µm像素, 99pJ/像素
对数梯度压缩QVGA图像传感器HOG特征低功耗物体检测
▸采用1.5或2.75位对数梯度压缩技术,减少25倍数据量
▸列并行读出与模拟循环行缓冲器实现多尺度像素合并
▸基于电容分压的比率数字转换器(RDC)实现对数梯度数字化
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 con- ventional CMOS imagers that feature linear and high-resolution ADCs, our readout scheme extracts logarithmic intensity gradi- ents at 1.5 or 2.75 bits of resolution. This eliminates unnecessary illumination-related data and allows the HOG feature descriptors t ob ec o m p r e s s e db yu pt o2 5× 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 × 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- µmC I S process with standard 4-T 5-µm 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.