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

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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.