Learning and Intelligent Systems: Intelligent Visual Grouping: Basic Mechanisms, Models, and Applications

学习与智能系统：智能视觉分组：基本机制、模型和应用

• 批准号: 9720305
• 负责人: Robert Shapley
• 金额: $ 87.5万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-10-01 至 2002-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9720305&HistoricalAwards=false
• 关键词: Learning; Intelligent; Systems; Visual; Grouping

IBN-9720305 PI: SHAPLEY This project is being funded through the Learning & Intelligent Systems Initiative. The questions involve vision and learning in the central nervous system. The project investigates how the brain represents and processes perceptual information, and the adaptive changes that occur when the system learns and improves its performance. Here the visual system is used as a gateway into the workings of the brain, employing methods from psychophysics, neurophysiology, mathematics and engineering. The work focuses on visual grouping, which is the ability of the visual system to link together local elements of the visual image into coherent wholes. Grouping is one of the most fundamental aspects of human vision, and the goal of this work is to obtain a theory of visual grouping that will explain the physiological and psychophysical data, and lead to new technological ideas to be applied in intelligent artificial systems. Results will be important because understanding the computations in the brain that produce grouping would be a leap forward in our understanding of brain function, and of any systems that can adapt to experience. This work will therefore have an impact in designing learning materials and in the optimal methods of presenting information, and in the design of the next generation of computer vision systems and intelligent control systems. This project is supported in part by the NSF Office of Multidisciplinary Activities in the Directorate for Mathematical & Physical Sciences.

IBN-9720305 PI：SHAPLEY 该项目由学习智能系统倡议资助。 这些问题涉及中枢神经系统的视觉和学习。 该项目研究了大脑如何表示和处理感知信息，以及当系统学习和提高其性能时发生的自适应变化。 在这里，视觉系统被用作进入大脑工作的门户，采用心理物理学，神经生理学，数学和工程学的方法。 这项工作的重点是视觉分组，这是视觉系统的能力，将视觉图像的局部元素连接在一起，形成连贯的整体。 视觉分组是人类视觉最基本的方面之一，这项工作的目标是获得一种视觉分组理论，该理论将解释生理和心理物理数据，并导致新的技术思想应用于智能人工系统。 结果将是重要的，因为理解大脑中产生分组的计算将是我们理解大脑功能和任何能够适应经验的系统的一个飞跃。 因此，这项工作将对设计学习材料和呈现信息的最佳方法以及下一代计算机视觉系统和智能控制系统的设计产生影响。 该项目得到了数学物理科学理事会多学科活动NSF办公室的部分支持。