Programmable Camera Systems for Transport-Aware Imaging

用于传输感知成像的可编程相机系统

• 批准号: RTI-2018-00762
• 负责人: Kutulakos, Kiriakos
• 金额: $ 10.82万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=642279
• 关键词: Programmable; Camera; Systems; Transport; Aware

While the last decade has seen a major race to improve the resolution, optics and noise properties of cameras, the future will likely hinge on what else a camera can offer. In the past five years at the University of Toronto, we have been exploring a new class of computational cameras whose key property is that they are "transport-aware." Unlike conventional cameras which record all incident light, transport-aware cameras can be programmed to block some of that light, based on the actual 3D paths it followed through a scene. Our initial work on harnessing the power of these cameras has demonstrated never-seen-before capabilities with applications to rapid 3D shape acquisition; robust time-of-flight imaging; visual material analysis; scene understanding; robotic and/or automotive navigation; industrial inspection; and even monitoring a city's electrical grid.

虽然在过去的十年里，人们在提高相机的分辨率、光学和噪声特性方面展开了一场重大的竞赛，但未来可能取决于相机还能提供什么。在过去的五年里，在多伦多大学，我们一直在探索一类新的计算相机，其关键属性是，他们是“运输意识。“与记录所有入射光的传统相机不同，运输感知相机可以根据它在场景中的实际3D路径进行编程，以阻挡部分光线。我们在利用这些相机的能力方面的初步工作已经展示了前所未有的能力，可应用于快速3D形状采集;强大的飞行时间成像;视觉材料分析;场景理解;机器人和/或汽车导航;工业检测;甚至监控城市电网。