ACTIVITY DEPENDENT PROCESSING IN THE FLY EYE

蝇眼中的活动依赖性处理

• 批准号: 7959865
• 负责人: STEVEN F BARRETT
• 金额: $ 7.38万
• 依托单位: UNIVERSITY OF WYOMING
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7959865
• 关键词: Area; Biological; Breathing; Centers of Research Excellence; Computational algorithm; Computer Retrieval of Information on Scientific Projects Database; Computer Vision Systems; Development; Exhibits; Eye; Foundations; Funding; Grant; Image; Insecta; Institution; Knowledge; Medical; Military Personnel; Movement; Neurosciences; Organism; Photoreceptors; Probability; Process; Prosthesis; Research; Research Personnel; Resolution; Resources; Retinal; Robot; Science; Source; Structure; Synapses; System; Techniques; United States National Institutes of Health; Vision; Visual Cortex; Wheelchairs; analog; base; design; digital; image processing; imaging Segmentation; interest; novel strategies; relating to nervous system; sensor; success

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The early vision system of insects as well as many higher level organisms exhibit interesting phenomena and features such as analog preprocessing, parallel structure, and sub-pixel resolution. Early vision is defined as the vision processes that occur within the first few cellular synapses beyond the photoreceptor layer. These features allow for the rapid extraction of image primitives: object edges, boundaries, image segmentation, and movement parameters. This analog, parallel approach to vision provides advantages over current digital-based imaging system. The same type of object information can be extracted with a digital-based system; however, extraction usually requires multiple passes of image processing techniques that must be exhaustively applied pixel-by-pixel to an image. We propose a new approach to the challenge of vision sensor development which takes its inspiration from the obvious success of biological vision systems. This project will use a similar evolutionary, system-level development that has resulted in robust, adaptable vision for so many biological organisms. In this biologically-based systems approach, the sensor (the "eye") and the computational subsystem (the "visual cortex") will be developed together. The sensor design and the computational algorithm design will be made to evolve together as a synergistic, mutually optimized pair; we believe this will greatly increase the probability that successful computer vision will be achieved for a wide variety of medical, commercial, and military applications. This project will advance the state of science in several ways. First, greater understanding of biological vision will be a benefit. The preprocessing in retinal neural layers and the final processing in the visual cortex is only partially understood today. By creating analog circuitry that accomplishes some of the preprocessing and computational algorithms that implement the final processing, more complete knowledge of biological vision will be obtained. Second, a more capable and robust computer vision system suitable for intelligent navigation to be achievable for a wide variety of mobile applications such as autonomous wheelchairs and robot movement in hazardous areas is expected. Furthermore, we believe this research will provide the foundation for the development of a vision prosthetic system.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 昆虫的早期视觉系统以及许多高级生物都表现出有趣的现象和特征，例如模拟预处理，平行结构和亚像素分辨率。 早期视力定义为在光感受器层以外的前几个细胞突触中发生的视觉过程。 这些功能可以快速提取图像原始素：对象边缘，边界，图像分割和运动参数。 这种模拟，平行的视觉方法比当前基于数字的成像系统具有优势。 可以使用基于数字的系统提取相同类型的对象信息；但是，提取通常需要多个图像处理技术，必须详尽地将像素像素应用于图像。 我们为视觉传感器开发挑战的挑战提出了一种新的方法，该方法从生物视觉系统的明显成功中汲取灵感。该项目将使用类似的进化，系统水平的发展，从而对许多生物生物产生了强大的适应性愿景。在这种基于生物学的系统方法中，将共同开发传感器（“眼”）和计算子系统（“视觉皮层”）。传感器设计和计算算法设计将作为协同，相互优化的对一起发展。我们认为，这将大大增加成功的计算机愿景，以实现多种医疗，商业和军事应用的可能性。该项目将以几种方式推进科学状态。 首先，对生物愿景的更多了解将是一个好处。如今，视网膜神经层的预处理和视觉皮层中的最终处理仅部分了解。 通过创建完成一些实施最终处理的预处理和计算算法的模拟电路，将获得对生物视觉的更完整的了解。 其次，预计将在危险区域中的多种移动应用（例如自主轮椅和机器人运动）来实现一个适合智能导航的功能强大，更强大的计算机视觉系统。 此外，我们认为这项研究将为开发视觉体系的发展奠定基础。