Collaborative Research: Visual Cortex on Silicon

合作研究：硅上视觉皮层

• 批准号: 1317560
• 负责人: VIJAYKRISHNAN NARAYANAN
• 金额: $ 482.35万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1317560&HistoricalAwards=false
• 关键词: Collaborative; Research; Visual; Cortex; Silicon

The human vision system understands and interprets complex scenes for a wide range of visual tasks in real-time while consuming less than 20 Watts of power. This Expeditions-in-Computing project explores holistic design of machine vision systems that have the potential to approach and eventually exceed the capabilities of human vision systems. This will enable the next generation of machine vision systems to not only record images but also understand visual content. Such smart machine vision systems will have a multi-faceted impact on society, including visual aids for visually impaired persons, driver assistance for reducing automotive accidents, and augmented reality for enhanced shopping, travel, and safety. The transformative nature of the research will inspire and train a new generation of students in inter-disciplinary work that spans neuroscience, computing and engineering discipline.While several machine vision systems today can each successfully perform one or a few human tasks - such as detecting human faces in point-and-shoot cameras - they are still limited in their ability to perform a wide range of visual tasks, to operate in complex, cluttered environments, and to provide reasoning for their decisions. In contrast, the mammalian visual cortex excels in a broad variety of goal-oriented cognitive tasks, and is at least three orders of magnitude more energy efficient than customized state-of-the-art machine vision systems. The proposed research envisions a holistic design of a machine vision system that will approach the cognitive abilities of the human cortex, by developing a comprehensive solution consisting of vision algorithms, hardware design, human-machine interfaces, and information storage. The project aims to understand the fundamental mechanisms used in the visual cortex to enable the design of new vision algorithms and hardware fabrics that can improve power, speed, flexibility, and recognition accuracies relative to existing machine vision systems. Towards this goal, the project proposes an ambitious inter-disciplinary research agenda that will (i) understand goal-directed visual attention mechanisms in the brain to design task-driven vision algorithms; (ii) develop vision theory and algorithms that scale in performance with increasing complexity of a scene; (iii) integrate complementary approaches in biological and machine vision techniques; (iv) develop a new-genre of computing architectures inspired by advances in both the understanding of the visual cortex and the emergence of electronic devices; and (v) design human-computer interfaces that will effectively assist end-users while preserving privacy and maximizing utility. These advances will allow us to replace current-day cameras with cognitive visual systems that more intelligently analyze and understand complex scenes, and dynamically interact with users.Machine vision systems that understand and interact with their environment in ways similar to humans will enable new transformative applications. The project will develop experimental platforms to: (1) assist visually impaired people; (2) enhance driver attention; and (3) augment reality to provide enhanced experience for retail shopping or a vacation visit, and enhanced safety for critical public infrastructure. This project will result in education and research artifacts that will be disseminated widely through a web portal and via online lecture delivery. The resulting artifacts and prototypes will enhance successful ongoing outreach programs to under-represented minorities and the general public, such as museum exhibits, science fairs, and a summer camp aimed at K-12 students. It will also spur similar new outreach efforts at other partner locations. The project will help identify and develop course material and projects directed at instilling interest in computing fields for students in four-year colleges. Partnerships with two Hispanic serving institutes, industry, national labs and international projects are also planned.

人类视觉系统实时理解和解释各种视觉任务的复杂场景，同时消耗不到20瓦的功率。这个Expeditions-in-Computing项目探索了机器视觉系统的整体设计，这些系统有可能接近并最终超过人类视觉系统的能力。这将使下一代机器视觉系统不仅能够记录图像，还能够理解视觉内容。这种智能机器视觉系统将对社会产生多方面的影响，包括为视障人士提供视觉辅助，为减少汽车事故提供驾驶员辅助，以及增强购物，旅行和安全的增强现实。这项研究的变革性质将激励和培养新一代跨学科工作的学生，这些跨学科工作涵盖神经科学、计算和工程学科。虽然今天的几个机器视觉系统都可以成功地执行一个或几个人类任务--例如在傻瓜相机中检测人脸--但它们执行广泛视觉任务的能力仍然有限，杂乱的环境，并为他们的决策提供推理。 相比之下，哺乳动物的视觉皮层在各种目标导向的认知任务中表现出色，并且比定制的最先进的机器视觉系统至少高出三个数量级的能源效率。拟议的研究设想了一个机器视觉系统的整体设计，该系统将通过开发一个由视觉算法、硬件设计、人机界面和信息存储组成的综合解决方案来接近人类大脑皮层的认知能力。该项目旨在了解视觉皮层中使用的基本机制，以设计新的视觉算法和硬件结构，从而相对于现有的机器视觉系统提高功率，速度，灵活性和识别精度。为了实现这一目标，该项目提出了一个雄心勃勃的跨学科研究议程，将（i）了解大脑中目标导向的视觉注意机制，以设计任务驱动的视觉算法;（ii）开发视觉理论和算法，随着场景复杂性的增加而扩展性能;（iii）整合生物和机器视觉技术中的互补方法;（iv）开发视觉理论和算法。（iv）因应对视觉皮层的认识和电子装置的出现，发展一种新的电脑架构;及（v）设计人机界面，既能有效地协助最终用户，又能保障隐私和发挥最大效用。这些进步将使我们能够用认知视觉系统取代当前的摄像头，这些系统能够更智能地分析和理解复杂场景，并与用户动态交互。机器视觉系统能够以类似于人类的方式理解其环境并与之交互，这将使新的变革性应用成为可能。该项目将开发实验平台，以：（1）帮助视力受损的人;（2）提高驾驶员的注意力;（3）增强现实，为零售购物或度假访问提供增强的体验，并增强关键公共基础设施的安全性。该项目将产生教育和研究成果，通过门户网站和在线讲座广泛传播。由此产生的文物和原型将加强成功的正在进行的外展计划，以代表性不足的少数民族和公众，如博物馆展览，科学博览会，并针对K-12学生的夏令营。它还将推动在其他伙伴地点开展类似的新外联工作。该项目将帮助确定和开发课程材料和项目，旨在培养四年制大学学生对计算机领域的兴趣。还计划与两个西班牙裔服务机构、行业、国家实验室和国际项目建立伙伴关系。