提出一种高速事件过滤硬件架构，显著提升处理效率。
High Throughput Event Filtering: The Interpolation-based DIF Algorithm Hardware Architecture
- 基于距离与频率加权的插值算法，实现高效事件过滤。
- 1280x720分辨率下达403.39百万事件/秒吞吐量。
- 适用于高噪声环境，适合实时事件视觉系统部署。
近年来，事件视觉领域发展迅速，事件传感器性能不断提升，相关算法和应用也日益增多。然而，传感器数据流通常包含大量噪声，其程度受光照条件或传感器温度影响。本文提出一种基于距离与频率加权（DIF）的事件过滤硬件架构，并在FPGA芯片上实现。为评估算法性能，我们构建了一个新的高分辨率事件数据集并公开共享。实验结果表明，该架构在1280×720分辨率下达到403.39百万事件/秒（MEPS）吞吐量，在640×480分辨率下达428.45 MEPS。不同数据集下的受试者工作特征曲线下面积（AUROC）平均值在0.844至0.999之间，与当前最优滤波方案相当，但具有更高吞吐量和更广噪声适应能力。
原文摘要 · Abstract (English)
In recent years, there has been rapid development in the field of event vision. It manifests itself both on the technical side, as better and better event sensors are available, and on the algorithmic side, as more and more applications of this technology are proposed and scientific papers are published. However, the data stream from these sensors typically contains a significant amount of noise, which varies depending on factors such as the degree of illumination in the observed scene or the temperature of the sensor. We propose a hardware architecture of the Distance-based Interpolation with Frequency Weights (DIF) filter and implement it on an FPGA chip. To evaluate the algorithm and compare it with other solutions, we have prepared a new high-resolution event dataset, which we are also releasing to the community. Our architecture achieved a throughput of 403.39 million events per second (MEPS) for a sensor resolution of 1280 x 720 and 428.45 MEPS for a resolution of 640 x 480. The average values of the Area Under the Receiver Operating Characteristic (AUROC) index ranged from 0.844 to 0.999, depending on the dataset, which is comparable to the state-of-the-art filtering solutions, but with much higher throughput and better operation over a wide range of noise levels.
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