CRCNS data sharing: Human eye movements under natural free viewing

摘要：该奖项支持计算神经科学数据的准备和共享，作为一项探索性活动的一部分，旨在促进计算神经科学及相关领域的快速创新进展。本项目共享的数据是受试者在自然自由观看条件下观看视频片段时的眼球运动记录。数据将以原始和处理的形式提供，同时提供相应的视频刺激。将提供校准走线的代码。将提供代码、训练数据和验证数据，以促进预测算法的发展。这些数据最初是为了开发视觉显著性和视觉注意的信息论模型而收集的。预计它们将对神经科学，认知心理学和计算机视觉中的广泛问题有用。与信息理论模型相关的显著性图和原始特征图也将提供，以允许对量化哪些低级视觉特征可能更强烈地吸引人类注意和凝视感兴趣的用户轻松地进行定量分析。

Proposal No: 0747477PI: Laurent IttiAward Abstract:This award supports the preparation and sharing of computational neuroscience data as part of an exploratory activity aimed at catalyzing rapid and innovative advances in computational neuroscience and related fields. The data to be shared in this project are recordings of eye movements of subjects watching video clips under natural free viewing conditions. Data will be made available in both raw and processed forms, along with the corresponding video stimuli. Code will be provided for calibration of traces. Code, training data, and validation data will be provided to facilitate the development of prediction algorithms. These data were originally collected for development of an information-theoretic model of visual saliency and visual attention. It is anticipated that they will be useful for a broad range of questions in neuroscience, cognitive psychology, and computer vision. Saliency maps and raw feature maps tied to the information-theoretic model will also be made available, to allow users interested in quantifying which low-level visual features may more strongly attract human attention and gaze to easily perform quantitative analyses.