elaTCSF: A Temporal Contrast Sensitivity Function for Flicker Detection and Modeling Variable Refresh Rate Flicker

2024-12-03

ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia

AI Summary

This paper addresses the insufficient modeling of low-contrast flicker perception in display and lighting applications—particularly under variable refresh rate (VRR), peripheral vision, and low-spatial-frequency conditions where existing models fail. We propose the first extended temporal contrast sensitivity function (elaTCSF), jointly incorporating luminance, retinal eccentricity, and stimulus area. Methodologically, we systematically integrate these three factors into the TCSF framework, develop a spatial probability summation model, and introduce the first VRR-specific flicker detection benchmark dataset. Key contributions include: resolving the long-standing controversy regarding enhanced flicker visibility in peripheral vision; enabling high-accuracy prediction of low-persistence flicker in VR; empirically characterizing the flicker-free operational range for VRR systems; and supporting high-fidelity display and lighting design. Our elaTCSF consistently outperforms IDMS-TCSF across multiple benchmark datasets.

Technology Category

• Computer Vision: Low Level & Physics-based Vision
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Security and Privacy: Large-scale security measurements

Abstract

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.

Problem

• Extend TCSF to model flicker with luminance, eccentricity, area.
• Create first variable refresh rate flicker detection dataset.
• Resolve debate on flicker visibility in peripheral vision.

Innovation

• Extends TCSF with luminance, eccentricity, area
• Combines spatial probability summation model
• Trains on flicker datasets for VR, lighting