用分数阶电压动态模拟像素生命周期,提升事件相机仿真精度。
FracEvent: Event-Camera Simulation via Fractional-Relaxation Pixel Dynamics

- 基于分数阶松弛电压模型,还原像素级动态生命周期
- 生成事件时间结构更真实,下游任务性能优于现有方法
- 适合事件视觉研究、传感器仿真与算法验证场景
事件相机以微秒级时间分辨率异步记录亮度变化,但真实事件数据难以大规模获取,需专用传感器、精确同步和特定任务标注。因此事件相机仿真对事件视觉任务至关重要。现有模拟器多基于对比度阈值生成事件,部分添加滤波、随机噪声或人工调参,但常简化像素级时间演化过程,导致事件时序失真,影响下游迁移性能。本文提出FracEvent,通过分数阶松弛电压动力学建模像素生命周期。给定对数强度轨迹,FracEvent驱动一组紧凑的松弛模式,合并响应形成电压状态,通过连续电压轨迹定位阈值穿越点生成ON/OFF事件,并在更新参考值的同时保留底层记忆模式。该保留状态使残余电压响应与后续事件时序关联。我们在事件流对比及图像重建、光流估计等下游任务上评估FracEvent。跨多个数据集,FracEvent显著改善生成事件的时间结构,且在下游迁移任务中表现优于现有模拟器基线,证明其在事件相机仿真中的实用价值。
原文摘要 · Abstract (English)
Event cameras asynchronously report brightness changes with microsecond-level temporal resolution, but real event data remain difficult to collect at scale because specialized sensors, careful synchronization, and task-specific annotations are required. Event-camera simulation is therefore important to event-based vision tasks. Most practical simulators build on contrast-threshold event generation, some with additional filtering, stochastic noise, or hand-tuned sensor parameters. While effective, such formulations often simplify the temporal structure produced by the lifecycle of each pixel, which can distort event timing and weaken downstream transfer. We introduce FracEvent, an event simulator that models this pixel-level lifecycle with fractional-relaxation voltage dynamics. Given a log-intensity trajectory, FracEvent drives a compact stack of relaxation modes, combines their responses into a voltage state, emits ON/OFF events by localizing threshold crossings on the continuous voltage trajectory, and updates the reference while retaining the underlying memory modes. This retained state links residual voltage response to later event timing. We evaluate FracEvent through event-stream comparison and downstream transfer on image reconstruction and optical flow estimation. Across multiple datasets, FracEvent improves the temporal structure of generated events and achieves stronger downstream-transfer results than competing simulator baselines, showing its practical value for event-camera simulation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。