通过视频分析自闭症患者社交注视特征，提升诊断准确性。
Video-based Analysis Reveals Atypical Social Gaze in People with Autism Spectrum Disorder
- 用第三人称视频视角提取四种注视特征，避免眼动仪局限。
- 基于四类特征的分类器可有效识别自闭症者的注视异常。
- 适用于自闭症早期筛查与自然场景下的行为分析。
本研究对自闭症谱系障碍（ASD）人群的社交注视行为进行了定量且全面的分析。不同于依赖眼动追踪技术的传统第一人称视角，本研究采用自闭症诊断观察量表第二版（ADOS-2）访谈视频中的第三人称视角数据库，包含ASD个体与神经典型对照组。通过计算模型，从参与者和评估者视频中提取并处理了注视相关特征。实验样本按社交注视异常与否及是否确诊为ASD分为三组。本研究定量分析了四个注视特征：注视参与度、注视方差、注视密度图与注视转移频率。此外，我们构建了一个基于这些特征的分类器，用于识别ASD个体的注视异常。结果表明，在自然情境下分析社交注视具有有效性，凸显了第三人称视频视角在提升自闭症诊断潜力方面的应用价值。
原文摘要 · Abstract (English)
In this study, we present a quantitative and comprehensive analysis of social gaze in people with autism spectrum disorder (ASD). Diverging from traditional first-person camera perspectives based on eye-tracking technologies, this study utilizes a third-person perspective database from the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) interview videos, encompassing ASD participants and neurotypical individuals as a reference group. Employing computational models, we extracted and processed gaze-related features from the videos of both participants and examiners. The experimental samples were divided into three groups based on the presence of social gaze abnormalities and ASD diagnosis. This study quantitatively analyzed four gaze features: gaze engagement, gaze variance, gaze density map, and gaze diversion frequency. Furthermore, we developed a classifier trained on these features to identify gaze abnormalities in ASD participants. Together, we demonstrated the effectiveness of analyzing social gaze in people with ASD in naturalistic settings, showcasing the potential of third-person video perspectives in enhancing ASD diagnosis through gaze analysis.
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。