The recent studies showing that gaze features can be useful in the identification of Autism Spectrum Disorder (ASD), have opened a new domain where Visual Attention (VA) modeling could be of great help. In this sense, this paper presents a report of the Grand Challenge “Saliency4ASD: Visual attention modeling for Autism Spectrum Disorder”, organized at IEEE ICME’19, aiming at supporting the research on VA modeling towards this healthcare societal challenge. In particular, this paper describes the workflow, obtained results, and datasets and tools that were used within this activity, in order to help on the development and evaluation of two types of VA models: (1) to predict saliency maps that fit gaze behavior of people with ASD, and (2) to identify individuals with ASD from typical development.

最近的研究表明，凝视特征可用于识别自闭症谱系障碍（ASD），开辟了一个新的领域，视觉注意力（VA）建模可能会大有帮助。从这个意义上讲，本文提出了在IEEE ICME'19上组织的“ Saliency4ASD：自闭症谱系障碍的视觉注意建模”挑战赛的报告，旨在支持针对这一医疗保健社会挑战进行VA建模的研究。特别是，本文描述了此活动中使用的工作流程，获得的结果以及数据集和工具，以帮助开发和评估两种类型的VA模型：（1）预测适合注视行为的显着性图（2）从典型发展中识别具有ASD的个体。