CGV: Small: Inverse Light Transport Under Femto-Photography and Transient Imaging

CGV：小：在飞托摄影和瞬态想象下的逆光传输如何从单一视点恢复材料的双向反射率？这些看似不可能完成的任务是可能的，只要考虑到光速有限，并使用一种叫做飞托摄影的新型计算摄影技术。超快速成像的新进展为计算机图形学和计算机视觉中的光传输建模、表示和合成提供了巨大的新机会。通过分析场景对极短持续时间主动照明的瞬态响应，将有利于计算摄影和场景理解的研究。当全局光照达到平衡状态时，传统成像采用稳态响应。研究人员正在开发一种新的瞬态光传输理论框架，并正在使用时间分辨成像解决反问题。研究人员最近开发了第一个隐藏几何恢复的物理演示。该研究旨在通过开发一个数学框架来研究利用时间分辨成像的高维光传输，从而发展计算成像的一个新分支。这项研究为计算机图形/视觉和计算摄影领域带来了超高速成像。精细采样的时间维度为场景的几何和光度的建模和测量提供了一系列的研究方向，这些领域以前被认为是传统机器视觉无法达到的。时间分辨成像技术以新颖的方式利用了多路复用、稀疏化重构、状态空间公式、系统识别方法和参数化反射模型。总体而言，该研究将基于光传输的方法的边界推进了一个额外的（时间）维度，并希望表明5D光传输的正逆问题可以启发下一代成像硬件和算法。

CGV: Small: Inverse Light Transport under Femto-Photography and Transient ImagingRaskar, Ramesh, Massachusetts Institute of TechnologyHow can you photograph objects beyond the line of sight? How can you recover bidirectional reflectance of materials from a single viewpoint? These seemingly impossible tasks are possible by considering the finite speed of light and using a new type of computational photography called, Femto-Photography. New advances in ultra-fast imaging provide tremendous new opportunities in modeling, representing and synthesizing light transport in computer graphics and computer vision. Research in computational photography and scene understanding will benefit by analyzing the transient response of the scene to extremely short duration active illumination. Traditional imaging uses steady-state response where the global illumination has reached an equilibrium state. The investigators are developing a new theoretical framework for transient light transport and are addressing inverse problems using time-resolved imaging. The investigators have recently developed the first physical demonstration of hidden geometry recovery.The research aims to develop a new branch of computational imaging by developing a mathematical framework for studying higher dimensional light transport that exploits time-resolved imaging. This research brings ultra-fast imaging in the realm of computer graphics/vision and computational photography. The finely sampled time-dimension provides a range of research directions for modeling and measuring geometry and photometry of scenes that were previously considered beyond the reach of traditional machine vision. The techniques for time-resolved imaging exploit multiplexing, sparsity-exploiting reconstructions, state-space formulation, system identification methods and parameterized reflectance models in novel ways. Overall, the research pushes the boundaries of light transport based methods by an extra (time) dimension and hopes to show that forward and inverse problems in 5D light transport can inspire the next generation of imaging hardware and algorithms.