Programmable Camera Systems for Transport-Aware Imaging

虽然在过去的十年里，人们在提高相机的分辨率、光学性能和噪音特性方面进行了一场重大的竞赛，但未来很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，我们一直在探索一种新的计算相机，其关键特性是它们是“交通感知”的。与记录所有入射光线的传统相机不同，交通感知相机可以根据场景中实际的3D路径，对其进行编程，以阻挡部分光线。我们在利用这些摄像头的能力方面的初步工作已经展示了前所未有的能力，应用于快速3D形状获取、稳健的飞行时间成像、视觉材料分析、场景理解、机器人和/或汽车导航、工业检查，甚至监控城市电网。

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.