提出新模型elaTCSF,精准预测动态刷新率下的闪烁感知。
elaTCSF: A Temporal Contrast Sensitivity Function for Flicker Detection and Modeling Variable Refresh Rate Flicker
- 融合亮度、视角偏移和面积影响,改进传统闪烁敏感度模型。
- 在多组数据集上训练,首次建立可变刷新率闪烁检测数据集。
- 适用于虚拟现实、照明设计等领域,解决周边视觉闪烁可见性争议。
闪烁感知问题在照明与电子显示领域已持续百年。传统方法依赖临界闪烁频率(CFF),仅适用于高对比度闪烁(全亮/全暗)。为应对变化对比度闪烁,国际显示计量委员会(ICDM)提出时间对比敏感度函数 TCSF$_{IDMS}$,但忽略亮度、视角偏移和刺激面积等关键因素。现有模型在低空间频率下对闪烁检测表现不足。为此,本文扩展 TCSF$_{IDMS}$,结合新的空间概率叠加模型,构建包含亮度、视角偏移与面积影响的 elaTCSF 模型。在多个闪烁检测数据集上训练,并建立首个用于验证的可变刷新率闪烁检测数据集。此外,该模型可用于解释虚拟现实设备中低持续性导致的闪烁,识别无闪烁的可变刷新率工作范围,以及优化照明设计中的闪烁敏感度分析。
原文摘要 · Abstract (English)
The perception of flicker has been a prominent concern in illumination and electronic display fields for over a century. Traditional approaches often rely on Critical Flicker Frequency (CFF), primarily suited for high-contrast (full-on, full-off) flicker. To tackle varying contrast flicker, the International Committee for Display Metrology (ICDM) introduced a Temporal Contrast Sensitivity Function TCSF$_{IDMS}$ within the Information Display Measurements Standard (IDMS). Nevertheless, this standard overlooks crucial parameters: luminance, eccentricity, and area. Existing models incorporating these parameters are inadequate for flicker detection, especially at low spatial frequencies. To address these limitations, we extend the TCSF$_{IDMS}$ and combine it with a new spatial probability summation model to incorporate the effects of luminance, eccentricity, and area (elaTCSF). We train the elaTCSF on various flicker detection datasets and establish the first variable refresh rate flicker detection dataset for further verification. Additionally, we contribute to resolving a longstanding debate on whether the flicker is more visible in peripheral vision. We demonstrate how elaTCSF can be used to predict flicker due to low-persistence in VR headsets, identify flicker-free VRR operational ranges, and determine flicker sensitivity in lighting design.
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