CRI: II-New: Cognitive Mechanisms and Computational Modeling of Gaze Control During Scene Free Viewing, Visual Search, and Daily Tasks

CRI：II-新：场景自由观看、视觉搜索和日常任务期间注视控制的认知机制和计算模型

• 批准号: 1823276
• 负责人: Mubarak Shah
• 金额: $ 24.93万
• 依托单位: The University of Central Florida Board of Trustees
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823276&HistoricalAwards=false
• 关键词: CRI; II; New; Cognitive; Mechanisms

This project is to build an infrastructure to study visual attention and its applications at the University of Central Florida. The infrastructure will also enable larger-scale inquiries into high-level visual recognition problems in the vision sciences. The infrastructure of fixed and portable eye trackers will be used by several faculty and researchers across the University (e.g., Computer Science, Engineering and Computer Engineering, Psychology, Biomedical engineering and UCF Institute for Simulation and Training) to study human perception, cognition, learning, and motor control, as well as exploring applications in activity recognition, surveillance, and data summarization. The core goal of this infrastructure is to utilize gaze and eye tracking technology to understand mechanisms of attention from behavioral, neurophysiological, and computational perspectives and explore its applications in a wide range of problems in computer vision and psychology. The team utilizing the infrastructure has complementary expertise to address research encompassing computer vision, machine learning, human vision, imaging, and psychology. In particular, this infrastructure will be used to explore in what ways current attention models fail, how to remedy them, and discover new cues that attract gaze. The approach is a combination of cognitive and computational studies utilizing machine learning and computer vision techniques. New large-scale eye movement datasets and benchmarks will be constructed as part of this proposal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在建立一个基础设施，以研究佛罗里达大学的视觉关注及其应用。基础架构还将对视力科学中的高级视觉识别问题进行大规模的询问。固定和便携式眼镜跟踪器的基础设施将被大学的几位教师和研究人员（例如计算机科学，工程和计算机工程，心理学，生物医学工程和UCF模拟和培训研究所）来研究人类的认知，认知，学习，学习和运动控制，以及在活动中识别识别的应用程序，以及探索活动，探索活动，数据验证，数据和数据，以及数据，以及数据，以及数据，并验证数据，以及数据，以及数据。该基础架构的核心目标是利用目光和眼睛跟踪技术来理解行为，神经生理学和计算观点的注意机制，并在计算机视觉和心理学中的各种问题中探索其应用。利用基础设施的团队具有互补的专业知识来解决计算机视觉，机器学习，人类视觉，成像和心理学的研究。特别是，该基础架构将用于探索当前注意力模型失败，如何纠正它们以及发现吸引凝视的新提示的方式探索。该方法是利用机器学习和计算机视觉技术的认知和计算研究的结合。新的大规模眼动数据集和基准将作为本提案的一部分构建。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估标准通过评估来支持的。