光流传感器：一种方向选择性仿生视网膜设计
Optical Flow Sensor: A Direction-Selective Bionic Retina Design
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中文总结 AI 辅助
该研究提出一种像素级光流传感器集成电路，结合DVS的ON/OFF事件比较与时间差测量实现片上并行光流计算，功耗较FPGA加速DVS降低303倍，延迟达微秒级，输出数据量减少约3.3倍，适用于超高速低功耗视觉传感。
中文摘要 AI 辅助
光流表征视觉场中的运动，是生物与人工视觉系统中运动感知和跟踪的基础。生物视网膜通过局部ON/OFF通路和并行处理高效提取运动，而传统基于帧的光流依赖密集采样和全局计算，导致高延迟和高功耗。为克服这些局限，我们提出了像素级光流传感器（Optical Flow Sensor, OFS）集成电路，该设计结合动态视觉传感器（Dynamic Vision Sensor, DVS）的ON/OFF事件比较与时间差测量，可在片上实现全并行光流计算，光流专用的地址事件表示（Optical-flow-specific Address-Event Representation, OF-AER）接口支持低功耗、高吞吐量读出。基于CMOS的OFS，我们进一步提出基于光忆阻器的OFS以降低传感器功耗和面积开销。实验结果表明，与FPGA加速的DVS系统相比，所提OFS的功耗降低了303倍，同时保持微秒级延迟；此外，通过直接输出光流向量，OFS将输出数据量减少了约3.3倍，展现出在超高速、低功耗视觉传感应用中的巨大潜力。
英文摘要
Optical flow characterizes motion in the visual field and is fundamental to motion perception and tracking in biological and artificial vision systems. Biological retinas extract motion efficiently through local ON/OFF pathways and parallel processing, while conventional frame-based optical flow relies on dense sampling and global computation, resulting in high latency and power consumption. To overcome these limitations, we present a pixel-level Optical Flow Sensor (OFS) integrated circuit. The design combines Dynamic Vision Sensor (DVS) ON/OFF event comparison with time-difference measurement to enable fully parallel optical flow computation on-chip. An optical-flow-specific Address-Event Representation (OF-AER) interface supports low-power, high-throughput readout. \rev{Based on the CMOS-based OFS, we further propose optical memristor-based OFS to reduce sensor power consumption and area overhead.} Experimental results show that the proposed OFS achieves a 303$\times$ reduction in power consumption compared with FPGA-accelerated DVS systems while maintaining microsecond-level latency. Moreover, by directly outputting optical flow vectors, the OFS reduces output data size by approximately 3.3$\times$, demonstrating strong potential for ultra-high-speed, low-power vision sensing applications.
发表机构
- Peking University（北京大学）
机构由 AI 辅助整理，请以论文原文为准。
