用数字微镜装置实现视觉传感器高精度动态测试
Technical report of a DMD-based Characterization Method for Vision Sensors
- 基于数字微镜设备调控光强，实现时空可控的测试
- 可量化事件延迟、信噪比和动态范围等关键参数
- 适合神经形态视觉传感器研究者与标准制定者
本技术报告提出一种基于数字微镜装置（DMD）的新型视觉传感器表征方法，特别适用于事件驱动型视觉传感器（EVS）和天眸（Tianmouc）等类脑视觉传感器。传统图像传感器表征标准（如EMVA1288）因无法适配其动态响应特性而难以应用。本文设计了一套高速高精度测试系统，利用DMD调制空间与时间上的光强度，可在受控条件下对事件延迟、信噪比（SNR）和动态范围（DR）等关键参数进行定量分析。该方法提供标准化、可复现的测试框架，克服了现有评估技术的局限性。此外，该方法还具备生成大规模生物启发视觉数据集的潜力，为类脑视觉技术的统一基准测试奠定基础。
原文摘要 · Abstract (English)
This technical report presents a novel DMD-based characterization method for vision sensors, particularly neuromorphic sensors such as event-based vision sensors (EVS) and Tianmouc, a complementary vision sensor. Traditional image sensor characterization standards, such as EMVA1288, are unsuitable for BVS due to their dynamic response characteristics. To address this, we propose a high-speed, high-precision testing system using a Digital Micromirror Device (DMD) to modulate spatial and temporal light intensity. This approach enables quantitative analysis of key parameters such as event latency, signal-to-noise ratio (SNR), and dynamic range (DR) under controlled conditions. Our method provides a standardized and reproducible testing framework, overcoming the limitations of existing evaluation techniques for neuromorphic sensors. Furthermore, we discuss the potential of this method for large-scale BVS dataset generation and conversion, paving the way for more consistent benchmarking of bio-inspired vision technologies.
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